Data engineers have moved from the back room to the boardroom. In Poland’s 2025 tech scene, they are the builders of AI-ready infrastructure, wiring cloud, streaming, and governance so models don’t just run, they scale. From fintech and telecom to gaming, retail, and healthcare, employers are hunting for talent that can design resilient pipelines, clean chaotic data, and deliver reliable features in (near) real time.
Source: Databricks Press Release
With AWS Glue, Databricks, and Azure as the default stack, and Airflow, Astronomer and dbt running the orchestration, market signals are clear: companies want engineers who can ship fast, stay compliant, and keep data close to real time. The role is no longer “back-end support”; it’s a front-line enabler of product velocity, AI accuracy, and business strategy.
Poland’s data engineering market is being reshaped by AI adoption and the transfer of more complex projects to local teams. Market demand for data engineers shows that companies are scaling quickly but in an experience-first way, betting on proven professionals while closing the door to most junior entrants.
Methodology & baseline: Curioz data based on job ads and signed contracts. September 2024 is the baseline, all further movements are measured relative to that month.
Regular roles led the expansion, climbing steadily through spring and peaking at +120% in April 2025, before easing but still strong at +90% by August. Senior demand followed in tandem, from flat growth to +50% in March to August 2025 a late-summer re-acceleration of demand for seasoned engineers.
By contrast, Juniors demand slides steadily, bottoming out around -70% by August. Leadership offers have surged ~300% year over year as complex AI initiatives take root in Poland. Firms are concentrating headcount on senior ICs and leaders, tightening the on-ramp for juniors and curbing entry-level hiring.
What does that growth pattern add up to?
Looking specifically at job openings, the market’s structure reflects its momentum: Senior engineers consistently make up around 50% of roles, while Regular positions account for over 45%. This mix further confirms once again that companies are scaling with experienced talent rather than expanding at the early-career level.
Methodology: Curioz data from job postings and signed contracts. Monthly shares by seniority are computed as each level’s percentage of total records.
Junior roles show again downward trend, slipping from just over 3% in late 2024 to below 2% of total volume by summer 2025. This decline signals that the bar for entry is getting higher, likely because organizations under pressure to deliver AI projects have little room to train early-career staff. Leadership maintain a steady ~1% share, with a short-lived uptick during July’s volume dip, suggesting leadership demand is not the source of market swings. The proportional share changes little, even as overall posting volume grows.
Taken together, the trend lines show a market that is expanding in volume but not in structure: the weight remains firmly on Senior and Regular roles. The rising adoption of AI amplifies this pattern, as scaling data pipelines and ensuring governance require skills concentrated in mid-to-senior profiles. At the same time, Leadership demand is beginning to grow, although from a small base, to steer these initiatives, while Juniors remain sidelined.
Experience thresholds are easing as AI platforms mature and teams optimize for speed and cost. From Sep 2024 to Aug 2025, average required experience declines across most bands. Leadership rises through winter, then settles around 7.8 years by August, still above last autumn. Senior roles peak at 6.18 years in April before easing to 5.71 by August, about 0.5 years below the spring high. Regular roles hover near 4.5 years through winter and spring and slip to 3.95 by August, while Junior requirements trend down steadily from 3.10 to 2.25 years.
Net effect: titles remain, but years to title compress, with leadership the only band finishing higher year over year.
Methodology: Curioz data from job ads and signed contracts. For each month and seniority band, we calculate the weighted average required experience. Results are a combination of both directly specified experience and the average experience weighted by seniority requirements.
Curioz data shows the market tilting experience first at the top while streamlining elsewhere. As more complex AI and data programs run from Poland, companies need local heads of engineering to own architecture, compliance, and delivery, keeping leadership demand elevated. Senior roles are being recalibrated as mature cloud and data stacks shorten the learning curve and firms prioritize time to impact, widening the senior cohort even as the years required drift down. Junior entry points, meanwhile, are squeezed by automation and regulated workloads, nudging teams toward smaller, senior heavy squads.
Salary dynamics highlight how experience, skills, and platform specialization translate into market premiums, with clear differences emerging across roles and technologies. For Senior Data Engineers on B2B in Poland, platform premiums show clear tiers:
Baseline: Curioz median of ~160 PLN/h for a Senior Data Engineer on a B2B contract, without specifying technologies other than Python.
In short, Databricks still pays the most but is trending down from its late-2024 peak; Spark is the mover, building momentum through mid-2025; Glue is the dependable mid-teens staple; and ADF/Synapse continues to offer only a small, predictable uplift. As open table formats like Apache Iceberg spread across these stacks, the premium increasingly accrues to engineers who can design portable, governed lakehouse tables, sustaining Databricks’ platform edge, boosting Spark’s relevance, keeping Glue steady, and modestly lifting the baseline in Azure estates.
This view is supported by Curioz research and analytics, which show that data engineering has moved from backstage support to center stage in decision-making. Experienced engineers deliver AI-ready, governed, near-real-time data on Databricks, Azure, and AWS Glue, orchestrated with Airflow and dbt across fintech, telecom, gaming, retail, and healthcare. Hiring remains experience-first: Regular roles stayed elevated through summer, Senior demand re-accelerated, Leadership held steady in general seniority share, but increased in volume 3 times year-to-year, and Juniors shrank to a sliver as AI automates routine build-and-maintain work and accelerates “years-to-title.”
Experience is the premium, and seniors now sit at the center of Poland’s boardroom-grade data and AI.
Companies are clearly relocating more complex, regulated, high-impact processes to Poland, shifting the talent mix toward seasoned professionals and hands-on leaders who can design, govern, and scale platforms. Pay signals mirror platform value: Databricks retains a moderating premium from late 2024 levels, Spark’s momentum has resurged in 2025, AWS Glue remains a steady mid-tier uplift, and ADF/Synapse adds a small, predictable premium. Meanwhile, open table formats such as Apache Iceberg reward engineers who deliver portable, governed lakehouse data that boosts ROI, limits lock-in, and keeps senior ICs central to product velocity, AI accuracy, and cost control.
Most of 2025 is about real-time data pipelines, AI-ready architectures, automated transformations, and predictive analytics at scale. That’s exactly where a Data Engineer with modern stacks (Spark/Flink/Kafka/DBT/Cloud-native)and built-in guardrails excels.
Competitors are already moving. Add a TaaS QA Automation Engineer now to keep your edge, and compound it every sprint.
NOTE: This post is based on research by Inuits.it and Curioz.io, and has been crossposted on both platforms.