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Can AI Freeze Salaries?

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Rethinking Junior Talent in Tech

Generative AI is not just transforming business processes—it’s reshaping the tech job market at unprecedented speed. Roles that were once typical entry points are now automated with surgical precision. So, what happens to junior talent? And how should highly regulated industries like pharma adapt?

What Big Consultancies Are Signaling

Leading consultancies like EY, PwC, and Deloitte have recently frozen salaries for junior staff. This is not just a cost-saving move—it’s a response to the automation of repetitive, low-complexity tasks that used to be the foundation of junior roles.

“The market is not eliminating junior talent—it’s redesigning it with new skills and expectations.”

Tasks such as financial analysis, audit prep, and data collection are now being handled by algorithms. This forces companies to rethink how they build career paths and talent pipelines, especially in industries competing for high-demand tech profiles.

A Pharma-Specific Challenge

In pharma, the situation is even more complex. The demand for specialized tech talent is rising fast, especially in areas like:

  • Clinical and regulatory process automation: Reducing errors and timelines in clinical trials and documentation workflows.
  • Data governance and compliance: Ensuring traceability, quality, and regulatory alignment.
  • AI-driven R&D: Accelerating drug discovery and improving prediction of safety and efficacy.
  • Legacy-to-cloud integration: Modernizing infrastructure while retaining control of critical systems.

However, traditional junior talent doesn’t fit easily into this new context, where even entry-level roles require fluency in AI frameworks, DevOps, cloud, and advanced analytics.

So the question is: How do you build a talent pipeline without a pipeline?

From Functional Juniors to Specialized Juniors

Pharma IT and data leaders are starting to realize: generalist juniors are no longer enough. Today, companies need:

  • Junior hires with applied tech skills from day one
  • Faster learning curves and efficient onboarding cycles
  • Continuous training in AI, automation, and digital platforms
  • Hands-on experience with tools once reserved for senior profiles
“Automation has eliminated tasks—but not the need for talent. It has simply raised the entry bar.”

Junior talent must now deliver value immediately, without increasing fixed costs or losing flexibility.

A New Talent Architecture

This change demands a new approach to talent architecture, where the difference between junior and senior is no longer just about time, but about:

  • Adaptability to fast-changing tech environments
  • Autonomy in automated systems
  • Understanding of AI models in business context
  • A strong culture of self-learning and experimentation

Value is no longer based on years of experience—it’s defined by speed in acquiring new digital skills.

How Pharma Can Respond

To stay competitive, pharma companies must urgently rethink their tech talent strategy. Key actions include:

  • Redesigning hiring processes to prioritize tech-readiness even at junior levels
  • Creating internal learning paths to accelerate digital maturity
  • Partnering with universities and AI institutes to align training with real-world needs
  • Strengthening the business-tech connection, so even juniors understand their impact
“The goal isn’t to replace human talent—but to amplify its value from day one in increasingly automated environments.”

Hierarchies Are Out, Agility Is In

Freezing junior salaries is a symptom of a deeper shift: traditional career paths in tech are breaking down.

In their place, a new model is emerging—where automation coexists with agile, value-driven talent. Pharma, with its regulatory complexity and knowledge intensity, must embrace this shift.

Rethinking tech talent isn’t optional—it’s the only way to stay relevant in an AI-driven future.

Sources

Antonio Castaño

Autor Antonio Castaño Romero

Who Train the Trainers

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The race against time to fill the AI talent gap

Spanish universities are reacting urgently to a demand that has overwhelmed them: Artificial Intelligence has emerged so rapidly that up to 50% of specialized positions in this field remain unfilled. And the major paradox is that there aren’t even enough experts to train the next generation. This situation raises a critical question: how can we adapt training and talent acquisition models in technology—and especially in AI—particularly in sectors like pharmaceuticals, where innovation cannot be put on hold?

The gap is no longer just about talent, but about trainers

The shortage of AI talent is not a new phenomenon, but what has changed in the last two years is the pace: the labor market is moving faster than the education system. Official master’s programs are overwhelmed, top professionals are already working in the industry, and universities are even competing to recruit qualified professors.

“There are not enough PhDs with AI experience to teach the programs companies are demanding,” say several academic institutions.

In this context, the urgent question is not just how to train AI talent, but: who is going to do it?

Companies need hybrid profiles, but the system continues to produce vertical specialists

A data engineer, a computer scientist, and a pharmacist with machine learning knowledge might have three different educational backgrounds and never cross paths. Yet the pharmaceutical industry needs these worlds to come together:

  • Predictive models for clinical development
  • AI algorithms for personalized treatment
  • Automation of quality, production, or supply chain processes

The kind of talent the sector needs no longer fits into traditional profiles. This requires a deep review of how academic and corporate training programs are being designed.

What are universities doing to keep up?

Some institutions have begun taking drastic measures:

  • Rapidly updating master’s programs to include generative AI, cloud, and MLOps
  • Partnering directly with tech and pharmaceutical companies to bring in active professionals as guest lecturers
  • Outsourcing part of the training through bootcamps or private certifications

But even with these efforts, the challenge remains: training talent without enough qualified trainers creates a structural bottleneck.

“We’re training at full speed, and we’re still behind,” admitted the director of a master’s in AI.

And from the company’s perspective, what can be done now?

While the education system catches up, large companies cannot afford to wait. That’s why many are choosing to collaborate with specialized technology partners in AI, who can provide up-to-date talent, flexible teams, and integrated solutions. This approach allows companies to:

  • Reduce the average vacancy cost (AVC) by quickly filling critical roles
  • Embed continuous learning and expert support into real business projects
  • Avoid increasing fixed structure by using more scalable and adaptive collaboration models

This approach is becoming one of the most viable solutions to keep innovation moving and protect competitiveness, especially in highly regulated industries like pharmaceuticals.

The pharmaceutical sector is especially impacted by this shortage

In a context where breakthroughs increasingly depend on large-scale data processing, AI talent is not just a competitive advantage—it’s a business-critical need. Pharmaceutical companies must bring in professionals who understand AI, regulatory frameworks, biostatistics, and clinical knowledge. That makes the talent equation even more complex.

How do you train someone who needs to understand machine learning, healthcare regulations, and product lifecycle management?

This is where internal reskilling programs, partnerships with research centers, and investment in young talent become essential.

A model that falls short in the face of a shifting demand

What academia is teaching today may already be outdated in less than two years. The nature of AI itself demands professionals who are:

  • Agile in continuous learning
  • Equipped with critical thinking and tech ethics
  • Aware of the cross-functional role of data and AI within organizations

Meanwhile, the average vacancy cost (AVC) for AI roles is rising rapidly, directly affecting innovation and operational performance. Failing to fill an AI vacancy is not just an HR problem—it’s a real loss in competitiveness.

Who is really leading the future of training?

The challenge is no longer just about creating more master’s programs or bootcamps. The real question organizations must ask is: how does continuous training become part of business strategy?

  • Can a pharmaceutical company afford to wait for universities to catch up?
  • Should companies launch their own internal AI training programs?
  • Can external training keep pace with the speed of technological disruption?
“The professionals we need don’t exist yet. We have to create them, and that requires partnerships and strategic vision,” is increasingly heard in tech talent forums.

While universities struggle to update their programs and find qualified trainers, companies must move beyond traditional recruiting. The solution lies in growing talent from within, investing in flexible learning models, and understanding that AI training is no longer an academic task—it’s a business necessity.

Because in the end, the question remains the same: who will train the trainers… when there aren’t enough professionals to fill the key positions?

References and key documentation:

Antonio Castaño

Autor Antonio Castaño Romero

Why Tech Talent Doesn’t Stay

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The urgent need to redesign attraction strategies in Europe’s corporate landscape

The tech talent shortage isn’t just about lack of supply — it’s about unmet expectations.

Across Europe, and particularly in sectors like pharma, large companies are facing a growing paradox: they invest millions in digital transformation but fail to attract — let alone retain — the professionals capable of driving it forward. The issue isn’t only about salary or location. It’s structural and cultural.

“I’ll move abroad first”: a rational choice for many

It’s not about rebellion or restlessness. For many young tech professionals, leaving their home country has become a logical career move.

“Abroad, I get autonomy, diverse teams, international projects, and time to learn. Here, they want physical presence and strict hierarchy,” said a data engineer quoted by El País (Oct 2025).

What’s pushing this talent away from countries like Spain?

  • Lack of meaningful, impactful tech projects. Many tech professionals want to contribute to high-impact innovation — not just internal process upgrades with little visibility.
  • Slow and bureaucratic hiring processes. Long rounds of interviews, delayed feedback and indecision cause talent to drop out or accept faster offers.
  • Rigid contracts and limited flexibility. The traditional 9-to-6 in-office setup is no longer competitive. Tech talent wants autonomy and work models adapted to how they operate best.
  • Unclear career progression paths. Without visible growth opportunities or cross-functional projects, professionals look elsewhere to advance.
  • Command-and-control leadership that stifles innovation. Rigid hierarchies and lack of trust in autonomous work sap motivation and creativity.

Pharma: digital innovation without talent magnetism

Pharmaceutical companies lead the way in R&D investment and are rapidly adopting tech like AI, data lakes and automation. But when it comes to talent…

They often struggle to attract or retain tech professionals. Why?

  • IT and digital are still seen as support functions, not value drivers. They’re kept away from strategic decisions, stuck in maintenance roles.
  • Legacy hierarchies block agile decision-making. Tech professionals accustomed to fast-paced environments feel stuck in multi-level approval chains.
  • Workplace policies were designed for scientists, not developers. From working hours to incentive models, internal structures often mismatch tech expectations.
  • Projects are managed with a compliance mindset, not agile thinking. Innovation becomes boxed into risk-averse frameworks, slowing down creativity and iteration.
According to LinkedIn Talent Solutions (2025), health and pharma sectors show one of the largest gaps between digital investment and perceived attractiveness among next-gen tech professionals.

What does tech talent actually want?

It’s not just about money — or remote work. Digital professionals look for:

  • Purposeful projects with organizational visibility. They want to create value that’s seen, not buried in internal backlogs.
  • Agile, cross-functional teams. Collaboration across product, data, business and ops is essential to how they work.
  • Leaders with real tech background — not just people managers. Tech mentors are critical to growth and credibility.
  • Continuous learning and internal mobility. Without clear upskilling paths or role changes, they’ll find those opportunities elsewhere.
  • Autonomy to experiment and fail without punishment. Innovation depends on psychological safety and space to learn from mistakes.
“Tech professionals aren’t looking for just a job — they want a context where they can grow, fail, learn, and move forward without falling behind.”

Redesigning to attract: structural essentials

To attract top digital talent, organizations need more than strong recruiters. They need internal transformation:

  • Fast, value-driven hiring — not endless “culture fit” loops. Evaluate what talent can contribute, not how they dress or “fit in.”
  • Instant feedback cycles and visible growth paths. Without clarity and progression, engagement fades fast.
  • Flatter hierarchies and distributed leadership. Empowered teams make faster decisions and thrive on ownership.
  • Digital fully integrated into the business — not as back-office support. Tech teams want to be part of decision-making, not just execution.
  • Real flexibility: not just location, but how people work, lead and collaborate. Remote options aren’t enough — structural adaptability is the real differentiator.
McKinsey (2024) reports that 64% of digital talent turn down job offers due to lack of structural flexibility — beyond just hybrid policies.

Without cultural transformation, there is no digital transformation

The real barrier to attracting tech talent isn’t outside — it’s inside. The talent is out there. The needs are clear. What’s missing is that organizations evolve at the pace of the people they want to hire.

And if they don’t, they’ll be playing a global game with outdated rules — while others win with agility and relevance.

References

Antonio Castaño

Autor Antonio Castaño Romero

Your Data Stack Recruits (and Delivers ROI)

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How Lakehouse Architectures Are Driving Both Tech Talent Acquisition and Business Impact in Pharma

The shortage of data professionals in the pharmaceutical industry is undeniable, but one part of the problem remains hidden: legacy data infrastructures are pushing top talent away. Upgrading the data stack isn’t just about making IT happy — it’s about accelerating innovation, boosting operational efficiency, and driving measurable business results.

Today, we explore how the move toward Data Lakehouse architectures offers a strategic dual benefit: attracting top-tier tech talent while unlocking real organizational value.

Why Pharma’s Data Architecture Is No Longer Optional

In a data-driven world, outdated architecture equals lost agility, wasted resources, and missed opportunities.

Traditional Data Warehouses have served their purpose, but they now show serious limitations:

  • Poor scalability for growing data volumes
  • Limited integration of structured and unstructured data
  • Slow ETL processes and manual data transformations
  • High dependence on IT teams for insights

These limitations go beyond inconvenience — they directly impact critical areas like:

  • Clinical research and drug discovery
  • Pharmacovigilance and regulatory compliance
  • Supply chain optimization
  • Commercial efficiency and omnichannel analytics
“No pharma company can claim to be data-driven without a modern data architecture to support it.”

From Data Warehouse to Data Lakehouse: A New Standard

The Data Lakehouse combines the best of traditional warehousing with the flexibility of cloud-native lake architectures.

It enables companies to:

  • Process structured and unstructured data in real time
  • Democratize data access across business and IT teams
  • Eliminate duplicate pipelines between analytics and BI
  • Enhance traceability and data governance

The result: a future-ready infrastructure that supports faster insights, lower costs, and stronger compliance.

“Stop moving data to the tools — bring the intelligence to the data.”

What’s in It for Pharma? Measurable Business Benefits

Lakehouse architectures are more than a tech upgrade — they’re a business accelerator.

  • Shorter time-to-insight: Dashboards that connect R&D, QA, production, and marketing in minutes
  • Streamlined GxP compliance: Versioning, role-based permissions, and audit-ready tools
  • Reduced operational costs: Cloud-native, pay-as-you-go infrastructure
  • Faster innovation cycles: Ideal for AI/ML pilots, simulations, and RWE analytics
  • Empowered business teams: Self-service access to validated, secure data
“Every day of delay in data-driven decisions can cost millions in missed opportunities or inefficiencies.”

A Modern Stack Attracts Modern Talent

The most in-demand tech profiles don’t just want a good salary — they want cutting-edge tools and real challenges.

Today’s data professionals look for:

  • Modern platforms like Databricks, Snowflake, or BigQuery
  • Orchestration tools like Airflow or dbt
  • Automated DataOps and MLOps pipelines
  • Meaningful projects with business visibility

Companies offering this kind of environment hire faster, retain longer, and reduce Average Vacancy Cost (AVC) in critical roles.

Where to Start: Quick Wins Without Disruption

Modernization doesn’t require a full system overhaul. Leading pharma firms do it step-by-step, delivering value fast through small, high-impact moves:

  • Start with high-return use cases (pharmacovigilance, quality, commercial analytics)
  • Decouple critical processes and migrate them to validated cloud environments
  • Form mixed teams (IT, business, compliance) to ensure alignment
  • Build sandbox environments for AI and advanced analytics experimentation

Success depends on aligning tech, talent, and business goals from day one.

Modern Data, Smarter Pharma

Investing in a modern data stack in pharma is not just a tech decision — it’s a strategic move.

It directly affects the organization’s ability to innovate, stay compliant, operate efficiently, and attract top tech talent.

The goal is simple: empower pharma teams to stop asking if they can be data-driven — and start acting like it.

Sources and Recommended Reading

Antonio Castaño

Autor Antonio Castaño Romero

Can AI Replace Certain IT Roles in Pharma?

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An Early Look at the Impact of Madrid Tech Show 2025

As Madrid Tech Show 2025 approaches, artificial intelligence is set to become the star of the event—not only for its enterprise applications but also for its direct impact on technology talent. The pharmaceutical industry, already undergoing accelerated digital transformation, is no stranger to this disruption.

Is IT talent truly at risk from growing automation? Which functions could radically change? And what new roles are gaining strength? This article explores these questions from a realistic perspective, anticipating many of the key debates to take place in Madrid on October 29.

Replace or Transform? The Reality Behind IT Jobs

The narrative that generative AI will massively eliminate technical jobs has gained traction, but it doesn’t fully reflect reality. Instead, AI is reshaping the focus and skills required for IT professionals rather than erasing their value altogether.

One of the most anticipated sessions at the event, “Generative AI in Business: Challenges, Benefits, and Ethical Limits”, highlights this balance: automation yes—but with purpose, and without losing the human dimension of talent.

“AI doesn’t come to replace IT talent, but to push it toward more strategic and less operational capabilities.”

Pharma and Automation: Which Functions Are Changing?

In a highly regulated and sensitive industry like pharma, AI-driven automation is already transforming specific tasks. Sessions such as “Digital Transformation in Regulated Environments: AI and Automation in the Pharmaceutical Sector” will showcase how technology is reshaping critical areas such as:

  • Software testing (QA) automated with generative AI.
  • Regulatory documentation (GxP) generated with AI assistance.
  • Clinical data cleaning and normalization through intelligent algorithms.
  • First-level technical support handled by AI-powered chatbots.

These advances don’t eliminate roles, but they do change their function within the digital value chain.

The IT Roles Most at Risk (and How to Adapt)

Based on trends expected at the event, some IT roles are more exposed to a deep transformation of their tasks:

  • Manual QA Testers: partially replaced by intelligent testing platforms.
  • Support Technicians: routine issues resolved automatically by AI.
  • Data Engineers focused on repetitive data preparation tasks.
  • Technical Writers producing compliance documentation that can be AI-assisted.

The key will be evolving toward functions that combine technical expertise, business understanding, and the ability to collaborate with AI systems.

Emerging Roles in Pharma-AI Environments

Alongside automation, new roles are rapidly emerging and will be central to the future of IT work. Several will feature prominently in sessions at Madrid Tech Show:

  • Prompt Engineers: highlighted in “Generative AI in Business”, focused on designing effective prompts for regulated and medical use cases.
  • AI Product Owners: ensuring AI-driven products align with real business and compliance needs.
  • MLOps Engineers: featured in “AI + DevOps + MLOps: How the Software Lifecycle Is Changing”, key to integrating AI into pharma pipelines.
  • Data Governance Leads: essential for safeguarding ethics, privacy, and data quality.
“IT talent in pharma doesn’t disappear with AI—it shifts to more critical, strategic, and high-impact roles.”

Rethinking IT Talent Management: The Real Challenge

Sessions like “Digital Culture and Talent Management in the Age of AI” anticipate a vital conversation: technology alone does not transform organizations—talent does, when given the right conditions.

For pharma, this means rethinking:

  • Upskilling and reskilling programs aligned with new workflows.
  • Agile approaches to attracting specialized talent, often outside traditional channels.
  • Flexible organizational structures, mixing internal staff, consultants, and external experts.
  • Employer branding strategies, to compete against big tech and startups.

In short, AI won’t replace people—but it may replace talent models that don’t evolve.

An Opportunity to Lead Digital Transformation

Madrid Tech Show 2025 will serve as a mirror for many healthcare companies to assess whether they are truly prepared to compete in a data-driven, automated, and AI-powered world.

“AI doesn’t eliminate tech jobs—it eliminates jobs that don’t transform.”

For the pharma sector, this is both an opportunity and a responsibility: to lead the transition with vision, strategy, and bold investment in talent.

References

Antonio Castaño

Autor Antonio Castaño Romero

Q4 is here: have you reviewed your year-end planning?

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How to incorporate IT talent in pharma Q4 quickly, flexibly, and without a learning curve

The last quarter of the year is a race against the clock for many pharmaceutical companies. Strategic projects need to be closed, budgets must be executed, and IT and Marketing teams are under pressure to deliver with zero margin for error. In this context, incorporating IT talent in pharma Q4 becomes critical — yet highly complex: there’s no time for lengthy recruitment processes, internal training, or extended onboarding. What’s needed is efficiency, flexibility, and immediate expertise.

Q4: the quarter that puts IT teams to the test

Year-end pressure turns the pharmaceutical technology environment into a high-demand zone. Unlike other industries, pharma projects often involve regulated and business-critical components, especially those tied to CMS platforms, data solutions, automation, or AI initiatives linked to clinical trials and patient experience.

“You can’t deliver a December project with a profile still adapting to the culture, the sector, or the technology.”

The key challenge? Add talent that integrates seamlessly, has worked in similar environments, and can deliver from day one — with zero learning curve.

What really matters: speed, zero onboarding, and specific expertise

In Q4, companies don’t look for potential — they look for certainty. Project leaders need professionals who already master the technologies and practices required to close initiatives without friction.

  • CMS platforms in pharma (Adobe Experience Manager, Drupal, Sitecore). In-demand roles: solution architects, frontend developers in regulated environments, and content managers with compliance experience. They ensure corporate sites and medical portals are operational, localized, and compliant before year-end.

  • Data platforms and validated document management (Veeva, Salesforce Health Cloud, Snowflake). Most sought-after profiles: data engineers with validated environments experience, Veeva Vault administrators, and real world data analysts. They accelerate dashboards and critical integrations with no training delays.

  • AI models implemented in regulated environments. Key profiles: data scientists with clinical experience, MLOps experts able to deploy under regulatory frameworks, and automation engineers leveraging AI. They enable pilots in pharmacovigilance, clinical trials, or market analysis safely and at scale.

  • Cloud specialists for pharma environments. Essential roles: cloud architects, DevOps engineers, and cloud security specialists (AWS, Azure, GCP) adapted to pharma requirements. They enable rapid infrastructure deployments, cost optimization, and secure hybrid or multi-cloud setups.

Time is the scarcest resource in Q4, which forces companies to look beyond traditional recruitment channels.

Express integration models: beyond headcount

With headcount restrictions, more pharma companies are leaning on flexible models that add highly specialized talent without impacting their permanent structure.

  • Talent on-demand: senior profiles for weeks or months, not hired directly, yet fully embedded in teams.

  • External modular teams: specialized squads in a specific stack or solution, managed by tech partners.

  • High-performance freelancers: professionals with prior pharma experience working on defined deliverables.

“The companies that close projects most successfully in Q4 are those that stopped thinking in terms of hiring and started thinking in terms of integrating specialized talent.”

Urgency doesn’t have to mean improvisation

Planning for urgency is a core project leadership skill. Companies with validated talent networks, trusted partners, and defined contingency strategies are the ones that deliver — even under Q4 pressure.

Reducing Average Vacancy Cost (AVC) is achievable by minimizing the time from need identification to profile activation and eliminating unproductive learning curves.

Is this becoming the new standard for IT talent integration?

Q4 2025 points to a trend that extends beyond year-end. Speed, specialization, and frictionless integration are shifting from emergency fixes to standard practice.

In pharma — where time also impacts patient health — ensuring talent arrives pre-trained, sector-aware, and ready to deliver immediate value is no longer optional: it’s a strategic necessity.

“The best talent isn’t always actively job hunting. But they are willing to join impactful, well-managed projects — and today that’s easier than ever with the right integration model.”

References and further reading

Antonio Castaño

Autor Antonio Castaño Romero

Have You Already Planned Your IT Team’s Vacation?

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5 keys to protect continuity and retain top tech talent

Summer is here, and while some departments slow down, IT teams keep running like nothing ever stopped. In highly regulated and critical environments like pharma, vacations must be handled with surgical precision. If they aren’t, they can become a silent threat to operations, morale, and talent retention.

Vacation planning in IT isn’t operational management—it’s strategic leadership.

1. Digital disconnection: a right or a myth?

In hybrid and remote IT teams, digital disconnection often exists only on paper. The real challenge is not giving time off, but ensuring people can truly disconnect.

  • Remote setups blur boundaries. A developer on vacation might still check Slack, simply because they’re “digitally visible”.
  • Tools like Microsoft Teams or service ticketing platforms allow for smart out-of-office settings, muted mentions, and status automation.
  • Properly set automations and backup processes prevent the need to interrupt someone who is off.

“A professional who doesn’t disconnect won’t recover; and one who doesn’t recover, eventually burns out.”

2. Burnout has a price—and vacations are the cheapest solution

Time off is not a reward. It’s a preventive system against burnout.

  • Deloitte (2023) reported 64% of tech professionals experienced burnout last year.
  • In pharma tech environments, where quality and compliance are non-negotiable, burnout-driven errors can be very costly.
  • Well-scheduled vacations reduce Average Vacancy Cost (AVC) and help retain critical roles longer.

When a DevOps engineer postpones vacation all summer due to workload and ends up quitting in September—right before an audit—the hidden cost becomes visible. Prevention, not reaction, is what makes the difference.

3. Who’s in charge when everyone’s away?

Critical infrastructure doesn’t rest—but people must.

  • Effective vacation planning includes documented protocols, coverage plans, and escalation maps. If the cybersecurity lead is away, someone else must know how to handle incidents.
  • Tools like Ansible or Jenkins (automation), or AI-based monitoring platforms like Dynatrace and Datadog reduce the need for human intervention.
  • Smart on-call rotations ensure stability without overloading a few key players.

“The most expensive backup is the talent that never returns from vacation—because they never took it.”

4. What your vacation data says about your team

Unused vacation days reveal more about team health than any engagement survey.

  • KPIs like vacation usage rate, leftover PTO days, or leave clustering during peak periods are early warnings. If 40% of your dev team schedules time off in September, there’s likely a hidden summer overload.
  • HR analytics can help spot inequality in leave access, detect burnout trends, and predict turnover risk.
  • In high-pressure sectors like pharma-tech, vacation data should be part of workforce planning.

5. Agile and time off: not mutually exclusive

Vacation planning fits agile workflows—with the right adjustments.

  • Agile teams must factor time off into sprint planning from the start.
  • Tools like Jira help adjust team capacity and velocity during lower availability periods.
  • Asynchronous work and hybrid models allow teams to structure more sustainable deliverables.

Rather than assigning full workload to a half-staffed team, it’s smarter to reprioritize the backlog and focus on independent, lower-dependency tasks aligned with actual capacity.

More than a break—vacation as a business strategy

Vacation management isn’t about logistics; it’s about cultural maturity. In pharma and other high-demand tech industries, well-rested teams aren’t a luxury—they’re a requirement for long-term quality and innovation.

When a tech team rests well, it performs better, stays longer, and contributes more sustainably.

Sources:

Antonio Castaño

Autor Antonio Castaño Romero

Upskilling strategies: how to develop IT talent in Pharma without losing it later

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In the pharmaceutical industry, investing in the continuous development of IT talent is a strategic necessity. But there’s an increasingly clear trend: training digital profiles does not guarantee their retention. In many cases, upskilling has become a fast lane out for top talent.

Is the pharma sector unintentionally accelerating talent loss through its own development policies? This article explores that paradox, combined with two key trends shaping the landscape: the rise of digital nomads and the seasonal appeal of summer flexibility for highly skilled professionals.

When training is not enough

Many pharmaceutical companies have made technical training a priority. E-learning platforms, certifications in cloud, AI, or DataOps, internal bootcamps… However, the data shows that the most highly trained profiles are also the most likely to leave if they can’t apply what they’ve learned.

“Upskilling without organizational change can become a résumé booster funded by the company.”

IT talent — especially high-level profiles like AI solution architects, data engineers, or cybersecurity experts — expect more than training: they want purpose, cutting-edge technology, and autonomy. If that doesn’t happen, the investment in training can become a direct pathway out, toward other companies or freelance projects.

What are the most skilled profiles looking for today?

Here are the key factors that intersect with upskilling when it comes to retention or departure:

  • Stimulating tech projects: the chance to apply what they’ve learned in real-world challenges.
  • Constant updates in tools and environments: training in cloud doesn’t help if they’re stuck in legacy systems.
  • Flexible or remote work models: especially valued among senior profiles.
  • Visibility and impact of the IT role on the business: they want to see real business results, not just tasks.

In the pharmaceutical sector, where structures tend to be more rigid and regulated, these expectations often clash with corporate culture, making it harder to retain talent despite training investment.

The digital nomad profile and its impact on pharma

At the same time, a powerful trend is taking shape: highly qualified IT professionals who prioritize geographic freedom and purpose-driven projects over stability and salary. This is the rise of the digital nomad, and Spain has become one of their preferred destinations.

So what does this have to do with pharma? More than it seems.

  • Málaga, Valencia, and Palma de Mallorca have built thriving digital hubs offering connectivity, community, and quality of life. Many digital health and biotech startups operate from these locations with fully remote models.
  • These professionals — cloud engineers, AI specialists, DevOps, data scientists — only choose pharma projects if they offer real remote work, updated tech stacks, and professional autonomy.
  • The increase in freelance, consultant, or interim digital roles offers alternatives to traditional employment contracts.
“Talent hasn’t stopped learning; it’s just stopped accepting rigid structures.”

To attract them, some pharma organizations are redefining their IT talent strategies with agile models, temporary roles, and asynchronous work setups. But most still lag behind.

Summer as an emotional catalyst for career change

July and August are more than just vacation months. For many IT professionals — especially younger ones or those with a global mindset — summer is the ideal time to reflect on their careers and prioritize lifestyle.

And what happens when they realize they can work from Cádiz, Tenerife, or Menorca, without ever setting foot in a corporate office again?

  • Searches for “remote IT jobs” in Spain increase by around 30% during summer.
  • Flexible work platforms like Malt and Workana show spikes in new professional signups between June and September.
  • Companies with fully remote or “summer flexible” policies (allowing work from anywhere during summer months) are attracting profiles that are hard to find the rest of the year.
“Searches for ‘remote IT jobs’ in Spain increase by around 30% during summer.”

The key question is: Is the pharma sector ready to compete with that kind of value proposition?

What if upskilling also had a territorial component?

Here lies an underused opportunity: leveraging upskilling as a territorial attraction tool, by offering advanced training linked to flexible locations, partnerships with tech hubs, or remote learning residencies.

“Training is no longer just about teaching; it’s about connecting professional development with lifestyle and community.”

Pharma companies that embed this vision into their IT talent strategy — combining learning, flexibility, and purpose — will gain a real advantage in a market where competition is no longer just about salary, but experience.

5 ways to avoid training talent… for someone else

  • Link every upskilling program to a clear internal career roadmap.
  • Create hybrid business-tech roles that showcase real impact.
  • Offer real geographic mobility options, especially in summer.
  • Build continuous learning journeys, not one-off training events.
  • Highlight success stories from IT profiles who have grown inside the company.

Training without retention means losing the ROI. Today’s IT talent isn’t retained through courses. It’s retained with vision, flexibility, and environments where learning matters.

Sources and further reading:

Antonio Castaño

Autor Antonio Castaño Romero

How to Manage Your Pharma Tech Needs Without Losing Control

Rows of iMac computers and white chairs in a modern office
Reading Time: 3 minutes

Managing tech talent in the pharmaceutical sector without inflating costs or losing operational agility has become one of the industry’s greatest challenges.

Tech demands in pharma are growing faster than most internal teams can handle. AI, advanced data systems, automation, and next-gen CMS & DXP platforms are redefining operations. Yet, as innovation accelerates, recruiting and onboarding the right tech talent isn’t keeping up—creating bottlenecks and driving up hidden costs.

Why is tech talent management so hard in pharma?

The real challenge is not just finding qualified professionals, but integrating them quickly and efficiently—without bloating the organization or breaking compliance frameworks.

  • Internal hiring processes are slow, often taking over 90 days for key roles.
  • The Average Vacancy Cost (AVC) for tech roles in pharma can exceed €35,000 per open position.
  • Full outsourcing may speed things up but risks disconnecting teams from critical business processes.
“The real goal isn’t just to hire talent—it’s to integrate them smoothly into highly regulated and quality-driven environments.”

What’s actually working? Four flexible models that deliver results

Top pharma companies are adopting new, more agile ways to meet their tech talent needs—without losing control or compliance.

Here are four of the most effective approaches being used today:

1. Talent-as-a-Service (TaaS)

On-demand access to specialized tech professionals, without adding to the permanent headcount.

This model is perfect for high-intensity projects, migrations, or AI rollouts, offering fast onboarding with limited structural risk.

  • Scales with project demand.
  • Faster onboarding, lower friction.
  • Maintains cost control and delivery deadlines.
“TaaS activates the right talent at the right time—no permanent overhead required.”

2. Hybrid internal/external teams

External experts embedded within in-house teams, fostering true collaboration.

This approach blends external agility with internal know-how, while maintaining quality and compliance alignment (GxP standards).

  • Supports knowledge transfer and internal upskilling.
  • Ensures regulatory process alignment.
  • Enhances delivery performance through blended teams.
“Hybrid teams combine external speed with internal business intelligence.”

3. Fractional models

Senior professionals working part-time or on specific objectives.

Ideal for strategic leadership roles in architecture, data governance, or AI—without the cost of a full-time hire.

  • High strategic impact, minimal cost.
  • Provides mentoring, oversight, and direction.
  • Extremely efficient for niche, high-level needs.
“Fractional talent delivers executive-level impact without the executive-level payroll.”

4. Squads-as-a-Service

Autonomous, cross-functional teams managed around specific client goals.

Best suited for innovation labs, new product development, or experimentation without disrupting core operations.

  • Agile and adaptable to shifting needs.
  • Efficient for digital product delivery.
  • Focused on results, not just resources.
“Squads execute innovation without putting stable operations at risk.”

Making it work: alignment is key

These models work—but only if the organization is culturally and operationally ready.

  • HR and IT must collaborate closely, aligning KPIs and long-term goals.
  • Knowledge management must be a priority, especially in fluid team structures.
  • Employer branding must evolve to support modern, flexible structures without internal friction.
“Flexible models only succeed when they’re rooted in culture, process, and shared purpose.”

Surviving and thriving: finding the right balance

Rigid hiring strategies no longer work in a fast-moving, regulated industry like pharma. The future lies in balancing agility, cost efficiency, and sustainability of knowledge.

Instead of relying solely on traditional hiring, companies must build scalable, hybrid talent structures capable of responding to innovation demands without compromising stability.

  • Rapid response to needs.
  • Operational control.
  • Cost-effective structures.
  • Long-term knowledge retention.

It’s not about hiring the best people—it’s about integrating them wisely into a high-demand, high-regulation ecosystem.

“True success means building scalable talent models that grow with the business—without breaking it.”

References

Antonio Castaño

Autor Antonio Castaño Romero

Generative AI in Pharma: The Technical Roles Healthcare Companies Are Already Demanding

Woman wearing virtual reality headset interacting with a holographic interface.
Reading Time: 3 minutes

Generative AI is no longer a futuristic vision. It’s a current strategic priority. Pharma companies are already demanding highly specialized technical profiles in generative AI to transform essential processes — from clinical trials to medical content creation, regulatory communication automation, and omnichannel marketing personalization.

A Growing Need for All Types of Pharma Companies

From global pharma giants to mid-sized healthcare companies, the sector is facing a clear dilemma: either adopt generative AI now or fall behind in productivity, innovation, and competitive edge. The gap between the potential of AI and its real implementation capacity lies in one factor: specialized talent.

“Generative AI isn’t an isolated innovation project — it’s a cross-functional driver of transformation in health organizations.”

Technology alone isn’t enough. What’s needed is expert IT talent capable of integrating generative AI solutions into the company’s existing data, compliance and content infrastructure — and that talent can be:

  • In-house, as part of the internal IT and data teams.
  • Provided by a specialized partner, offering flexibility, cost-efficiency and access to pre-trained professionals familiar with regulatory environments.
“Both options are valid, but specialized external talent enables faster execution without increasing fixed costs or compromising compliance.”

The Technical Profiles Pharma Is Looking For in 2025

  • Prompt Engineer with biomedical language expertise: Fine-tunes prompts in models like BioGPT or MedPaLM to generate accurate and context-specific clinical and regulatory outputs.
  • Machine Learning Engineer with clinical NLP experience: Develops and implements tailored models for extracting structured data from clinical records, scientific texts, and regulatory documents.
  • Generative AI Solutions Architect: Designs secure, scalable systems integrating GPT-4, Claude or similar models into internal platforms like Veeva Vault, SAP or Salesforce Health Cloud.
  • Data Engineer specialized in AI model pipelines: Builds data connections between internal sources (RWE, CRM, scientific publications) and generative AI systems to enable enterprise-grade performance.
  • AI Project Manager in regulated environments: Bridges data teams, compliance officers, clinical departments and IT to coordinate delivery and adherence to GxP, GDPR and other regulations.

Real-World Tools Being Used in Pharma

  • ChatGPT and GPT-4: Used for generating executive summaries, SOPs, pharmacovigilance reports, and medical content.
  • BioGPT: Microsoft’s biomedical language model, used for literature synthesis and clinical research assistance.
  • MedPaLM: A clinical question-answering model by Google DeepMind, supporting call centers and healthcare professionals.
  • Claude (Anthropic): Trusted for its alignment and explainability in sensitive regulatory and medical environments.
“These tools are powerful, but they’re only effective when integrated by skilled professionals into compliant, data-governed, and user-oriented ecosystems.”

Integration With IT and Marketing Is Essential

Hiring top AI profiles isn’t enough. They must work closely with IT and Marketing to create real business impact.

With IT:

  • Deploy models in secure environments (on-prem, AWS, Azure, GCP).
  • Ensure traceability and auditability through robust data architecture.
  • Integrate legacy systems like ERPs or clinical CRMs with new AI-powered layers.
  • Enforce data governance and regulatory compliance (HIPAA, GxP, GDPR).

With Marketing:

  • Personalize and scale approved medical content across channels.
  • Enable message variation through prompt-based generative models.
  • Integrate generative AI with Adobe Experience Manager, Salesforce Marketing Cloud, WordPress VIP, or Veeva CRM to deliver faster, more relevant content.
  • Speed up time-to-market of compliant materials using AI-assisted review processes.
  • Test and personalize omnichannel journeys with real data and real-time learning.
“When technical AI profiles work side-by-side with IT and Marketing, generative AI becomes more than a trend — it becomes a sustainable competitive advantage.”

Those Who Understand Talent Will Lead the Innovation Curve

Generative AI platforms alone are not a guarantee of success. Pharma companies that invest in acquiring and integrating the right technical talent will be in a better position to:

  • Reduce time and cost in medical content creation.
  • Improve personalization across digital channels.
  • Accelerate regulatory compliance processes.
  • Generate validated clinical insights more efficiently.
  • Gain agility through hybrid models of in-house and external tech talent.
“In this new era of digital health, the real value lies not in the algorithm, but in the team that knows how to activate it.”

References

Antonio Castaño

Autor Antonio Castaño Romero