Unsure whether to hire a data engineer or a data scientist? You are not alone. Across Poland, companies are investing heavily in data talent, yet many are hiring in the wrong sequence, at significant cost.
This guide breaks down the key differences between the two roles, the right hiring order for your company’s stage of data maturity, and what you can expect to pay for each role in the Polish market in 2026.
Why European Companies Are Hiring Data Roles in the Wrong Order
Data engineers and data scientists are part of a rapidly growing market. The European Commission’s Data Market Study 2024–2026 values the European data market at roughly €178.5 billion in 2026. Around 20% of EU enterprises now use AI, according to Eurostat’s December 2025 survey, with adoption among large firms reaching roughly 55% and year-on-year growth of approximately 25%. Yet a BCG 2024 report found that 74% of companies still struggle to scale value from AI, often because they hired in the wrong order.
This is a pattern visible across Polish job boards and HR teams alike. A 2025 analysis of 8,086 data job postings found that 11% of titles are explicit hybrids, combining “Data Scientist / Data Engineer” into a single posting. This reflects both genuine resource constraints at smaller firms and widespread recruiter confusion, a pattern particularly common in Poland’s fast-scaling startup and mid-market sector, where data teams are often being built from scratch.
What Is a Data Engineer and What Is a Data Scientist?
Data engineers design and maintain the architecture that moves, stores, and prepares data. Data scientists analyse and model that data to produce insight and decisions. Without the infrastructure that data engineers provide, even the most skilled data scientist will struggle to deliver value.
Data engineers build and maintain the ETL (Extract, Transform, Load) pipeline that ensures data flows reliably from source to destination. Data scientists, meanwhile, build predictive models, perform statistical analysis, develop and test hypotheses, and apply machine learning where applicable. They also provide business insights for trends and forecasting, and data-driven recommendations with visualisation like dashboards to make complex findings accessible to non-technical audiences.
The overlap between the two roles is real. Both require strong Python and SQL, and both benefit from cloud familiarity. Beyond that, however, they diverge sharply.
Skills, Qualifications and Certifications: What to Look for in Each Role
While both roles typically require a computer science foundation, their paths diverge from there. Data engineers tend to come from computer and software engineering backgrounds while data scientists often are more focused on statistics and mathematics. A Masters degree is generally desirable for a data scientist, though certifications are valuable for both roles.
See more comparative info on the two jobs below:
While the two jobs are significantly different, smaller companies often advertise for one position but expect their new-hire to do the work of both. Some candidates do possess a blend of data engineering and data science skills, allowing them to handle both. But that is the rare exception, and hiring on that assumption can be a risk.
Should You Hire a Data Engineer or Data Scientist First?
A simple three-stage data maturity model can help recruiters push back proactively on hiring managers when the sequencing is off.
- Stage 1 is data chaos: spreadsheets, siloed systems, manual exports and no single source of truth.
- Stage 2 is data foundation: a basic warehouse, some pipelines, a BI tool where data is usable but not always trusted.
- Stage 3 is data intelligence: well-governed, documented, self-serve data that is ready for systematic prediction and optimization.
The honest picture for much of the Polish market is that a large proportion of firms, particularly outside Warsaw and the major tech hubs, are still at Stage 1 or early Stage 2. This is not a criticism. Poland’s data sector is maturing quickly, with Warsaw and Krakow now ranking among Central and Eastern Europe’s strongest tech talent markets. But it does mean that hiring a data scientist before the infrastructure exists is one of the most common and costly mistakes Polish recruiters and hiring managers make.
The Triggers That Tell You It Is Time to Hire
At Stages 1 and 2, the triggers for hiring a data engineer are clear: data volume is growing faster than current infrastructure can handle; data is fragmented across CRM, ERP, web analytics, and payment systems that do not communicate with each other; analysts are spending more time wrangling files than analysing them; or a cloud migration is underway or overdue.
At stage 2, moving into stage 3, the data scientist becomes the right next hire. The primary constraint is no longer access to reliable data but extracting forward-looking value from it. This is when business questions shift from “what happened?” to “what will happen?”
Timing hires to ROI is also worth considering, especially when budget is a concern. Data engineers typically deliver visible operational ROI within three to six months through reliable pipelines, faster dashboards, and fewer data disputes. Data scientists often need six to twelve months to move meaningful business KPIs, particularly in regulated sectors with longer validation cycles.
Poland’s Data Talent Gap: Why Demand Is Outpacing Supply in 2026
The European data job market has shifted decisively in favour of data engineers, and Poland reflects this clearly. A 2025 analysis found that engineering-oriented roles, including data engineers, ML engineers, and cloud and DevOps-adjacent positions, account for 53% of all data role postings across Europe, with data engineers outnumbering data scientists by roughly three to one. Poland’s own market mirrors this imbalance, with demand for pipeline-experienced, cloud-certified engineers outpacing the available talent pool in Warsaw, Krakow, Wroclaw, and beyond.
Filling those roles is proving difficult. Eurostat’s ICT employment data shows the ICT specialist workforce has grown over 60% since 2014, yet still falls short of demand. Skills mismatches are central to the problem. The market wants engineers with cloud certification, strong pipeline experience, and some understanding of ML infrastructure, and domestic supply in Poland has not yet caught up with the pace of demand.
Data Engineer and Data Scientist Salaries in Poland 2026
On salaries, the Polish market offers a notable advantage for international firms hiring remotely or on a nearshore basis. Senior data engineers in Warsaw or Krakow with strong AWS or Azure certifications and solid pipeline experience command rates substantially below equivalent hires in Amsterdam, Munich, or Dublin, while delivering comparable technical quality. For Western European firms building out data infrastructure, Poland represents one of the strongest sourcing markets in Europe.
For Polish employers competing for that same talent domestically, the picture is more challenging. Rates are rising as German, Dutch, and UK firms increasingly recruit Polish engineers on remote contracts, often at salaries that local firms struggle to match. The response must be proactive: clear career progression, flexible working, investment in training, and an employer brand that makes staying in Warsaw or Krakow as attractive as going remote for a Western European employer.
For data scientists, Poland’s market is more concentrated. The roles commanding the strongest salaries are clustered in finance, insurance, and the growing life sciences sector, mirroring the pattern seen in more mature Western European markets. Polish data scientists at senior level, particularly those with domain expertise in financial services or healthcare, are increasingly well-compensated by local standards, though a gap with Western European equivalents remains.
Can Verita HR Help You Find a Data Engineer or Data Scientist in Poland?
Verita HR has been placing data and technology specialists in Poland’s most competitive hiring markets for over a decade. Whether you need a pipeline engineer to build your data foundation or a data scientist to start extracting value from it, Verita HR has the network and the technical understanding to find the right fit.
Reach out to Verita HR’s data recruitment team today and let them introduce you to Poland’s strongest data engineering and data science candidates.
Author: Charley Mendoza
