Data Engineering in IT — CIS and Europe market
A Data Engineer is an engineer who designs the infrastructure for collecting, storing, transforming, and delivering data: ETL and ELT pipelines, data warehouses, streaming, orchestration. The core stack is Python and SQL, orchestrators Apache Airflow or Dagster, distributed processing via Apache Spark, streams via Apache Kafka, warehouses ClickHouse, Snowflake, BigQuery, Redshift, transformations via dbt. According to Zorky CRM, the IT market across CIS and Europe currently has 2380 active Data Engineer openings with a median salary of $6385/mo. The most in-demand technologies — python, databricks, spark, go, azure. 92% of positions are remote. Active employers — Yandex, Sber, Tinkoff, OZON, Wildberries, Avito, Kaspi, plus international data teams at Booking, Revolut, Databricks. Data refreshes daily from 1000+ sources.
Data Engineering is one of the core roles on IT teams. Over the last 3 months of observation across our 1000+ CIS and European sources this direction accounts for a significant slice of open IT jobs: 2 380 active positions as of the latest data refresh. Charts below render across the full available data window; text figures in the hero — the last quarter. On salary: median across the whole specialisation — $6 385/mo. Senior earns roughly 2.3× more than Junior — one of the most stable compensation gradients in IT. Data Engineering — one of the most remote-friendly IT specialisations: 92% of open positions are remote. There are 6 sub-specialisations inside this direction — a detailed breakdown of each follows below on this page.
Sub-specializations
Data Engineering breaks down into sub-specialisations: classic Data Engineer (ETL + warehouse), Big Data Engineer (Spark/Hadoop), Data Platform Engineer (infrastructure), DBA (database administration), Data Warehouse engineer (Snowflake/BigQuery), Streaming Engineer (Kafka). Each niche has its own salary range and toolset — click a card for detail.
Click to see detailed analytics.
Demand trend
Over recent weeks the Data Engineer direction has produced a steady flow of new openings. Fluctuations are normal (postings cluster at the start of the month); watch the overall trend, not individual spikes.
How many new jobs appear each week.
Seniority distribution — trend
How the share of Junior/Middle/Senior/Lead in open jobs shifts week over week. A trend toward Senior usually signals a mature specialization where companies look for ready-made talent; the opposite — a rise in Junior — signals expansion and ground-up team building.
Share of each level in % of all jobs with a stated grade per week.
Salary by level
Data Engineer salary ladder: Junior $2940/mo, Middle $5250/mo, Senior $6625/mo, Lead $7665/mo. The strongest pay growth is between Junior and Middle (picking up Airflow + Spark + a cloud platform).
Median salary (USD/month) at each grade plus the jump vs the previous one.
Biggest salary jump — between Junior and Middle (+78.6%).
Salary distribution — trend
The median Data Engineer salary on the market is $6385/mo. Most active jobs sit in the $4,000–8,000 band — the main mid-market segment. The $10K+ band is US-remote, Senior in crypto/fintech, Lead Data Platform.
What share of jobs each price band holds week over week.
67% of jobs are in the $5–8K range (the core market). High-end $8K+ segment: 15% — usually US-remote or senior-international roles.
Hiring geography
The leader by Data Engineer job count is 🇵🇱 Poland (1235 positions), followed by the major IT hubs of CIS and Eastern Europe. Important: this is the distribution across our parsing sources, not a global market estimate.
Job distribution by country.
These numbers reflect the distribution across the sources we parse. Poland often looks dominant because of dense NoFluffJobs / JustJoin.it / Pracuj coverage — the Polish IT market is genuinely large, but in our sample its share is overweighted relative to the real volume of all IT jobs in the region. Same caveat for other top countries: this is «where our parsers look», not «the true size of the market».
Remote / Hybrid / Office — trend
92% of Data Engineer jobs are full-remote; the rest are hybrid or office. Banks more often require hybrid because of compliance; startups and international teams — full-remote.
How the share of each work format shifts week over week.
92% — remote. Specialisation is well-adapted to remote format.
Top in-demand technologies
The top Data Engineer stack in 2026 is Python, SQL, Apache Spark, Apache Airflow, Apache Kafka. The Python + SQL baseline is required for everyone; specialisations follow: Spark (batch), Airflow (orchestration), Kafka (streaming).
Technology combinations
The most common technology pairs in Data Engineer postings: Python+SQL, Airflow+Spark, Kafka+ClickHouse, dbt+Snowflake, Spark+S3. If you are planning a learning roadmap, these combinations maximise market coverage.
Which pairs of technologies appear together most often in a single job.
Where we see these jobs
Data Engineer jobs surface across most major sources: web parsers (HH, Habr Career, Djinni, DOU, NoFluffJobs, JustJoin.it) provide the bulk of the volume. Telegram channels add an exclusive stream — data startups, ClickHouse-specialised positions, US-remote offers.
Data Engineering vs other directions
Data Engineer is one of the highest-paid IT specialisations by median. Click any direction's bar to compare salaries, stack, and dynamics in detail.
Volume of open jobs across IT directions.
Latest jobs
Latest open Data Engineer jobs — the most recent 10 positions with adequate description quality. The full list is available in our CRM or via the "see all" link below.
Key takeaways
- Demand is real: 2 380 Data Engineering jobs opened over the last 3 months — not a theoretical market live positions with active hiring.
- Salary anchor: median $6 385/mo. Senior earns noticeably more than Junior — compensation gradient is substantial.
- Remote-friendly: 92% of positions are remote. You can work from any country in the region without relocating.
- Top technology: python with 589 jobs — if you're just starting in Data Engineering begin there.
If you plan to grow in Data Engineering or hire a team — these numbers give a hands-on slice of the market. To watch in real time or get alerts on new jobs matching specific parameters — that's our CRM product for recruitment agencies and in-house teams.
What we can offer
If you work with Data Engineering jobs or you're in this role yourself — we can close a specific task. Pick a format, leave a contact — we reply within 24 hours.
Frequently asked questions
The most common questions about the Data Engineer market: salaries by level, stack (Spark vs Airflow vs Kafka), remote, comparison with Data Scientist and Analyst, where to start a career. Answers recompute automatically from current data.
How much does a Data Engineer earn in 2026?
The median Data Engineer salary across CIS and Europe is $6385/mo per Zorky CRM data from the last quarter (2380 active jobs). Pay depends on level and stack: Junior around $2940/mo, Middle $5250/mo, Senior $6625/mo, Lead $7665/mo. Data Engineers usually pay above Backend developers thanks to their specialisation in distributed systems and working with large data volumes. Senior engineers with Spark or Kafka experience at large banks (Sber, Tinkoff, Alfa) or marketplaces (OZON, Wildberries, Avito) often earn $7,000–10,000+/mo. In international data teams (Booking, Revolut, Databricks) — 30–50% above the local market. Salaries are normalised to USD, outliers filtered out.
What does a Data Engineer Junior, Middle, Senior, or Lead earn?
Data Engineer salary ladder (median USD/mo): Junior $2940, Middle $5250, Senior $6625, Lead $7665. Junior openings are few — companies expect newcomers to have already covered Python + SQL + ETL fundamentals via pet projects or after a reskilling from BI Analyst. The biggest jump is between Junior and Middle (picking up Airflow + Spark + a cloud platform). Lead Data Engineer often moves into Head of Data or Data Platform Lead — owning the data-infrastructure architecture of the whole company. We recommend newcomers: Python + advanced SQL + Airflow + one cloud (AWS/GCP) — that covers 80% of Junior–Middle openings.
How much do Data Engineers earn in Moscow and St Petersburg?
In Moscow and St Petersburg Data Engineers earn close to the market median — $6385/mo. Moscow traditionally pays more thanks to large banks (Sber, Tinkoff, Alfa) and marketplaces (OZON, Wildberries, Yandex Market); St Petersburg is close thanks to Avito and game studios with heavy data analytics. Remote is partial: 92% of jobs are full-remote, but banks often require hybrid because of compliance (work with PII and payment data). In Poland (Warsaw, Krakow) a Senior Data Engineer earns $5,500–9,500/mo. Berlin and Prague — €5,000–8,500. Almaty is a growing hub at $3,000–6,000. International remote contracts with Booking, Revolut, Spotify pay $7,000–12,000 for Senior.
What stack is most often required of a Data Engineer?
Top-5 technologies in Data Engineer postings across CIS and Europe: python, databricks, spark, go, azure. Required baseline skills: Python (advanced) and SQL (window functions, optimisation). The main orchestrator is Apache Airflow (the industry standard) or Dagster in newer teams. For distributed processing — Apache Spark (PySpark) or Flink. Streaming — Apache Kafka. Warehouses: ClickHouse (popular in RF), Snowflake, BigQuery, Redshift. Transformations — dbt (a growing trend). A cloud platform — one of AWS, GCP, or Azure is required at Senior. Docker, Kubernetes, Git, CI/CD are cross-cutting skills.
Who earns more — a Spark, Airflow, or Kafka specialist?
Most likely a specialist with experience across ALL three — people usually do not pick one. The most valuable Data Engineers on the market work with Spark (large-volume batch processing), Airflow (pipeline orchestration), Kafka (real-time streams). Per our sample: Senior with a Spark+Airflow+Kafka combo earns $6,500–10,000/mo. Narrow specialisations: Kafka engineer (streaming, event-driven) — highest pay $7,000–11,000/mo due to rarity. dbt / analytics engineer — a growing niche $5,000–8,500. Spark engineer (batch ETL) — steady Mid–Senior $4,500–8,000. ClickHouse specialists are especially valued in RF teams (Yandex, VK).
Can Data Engineers work remotely?
Partially: 92% of Data Engineer jobs are full-remote. Less than Backend or Frontend, because banks and fintech (Sber, Tinkoff, Alfa) often require hybrid or office due to compliance on work with PII and payment data — physical presence in a secured perimeter is needed. Marketplaces (OZON, Wildberries, Avito) — more often hybrid. International product teams (Booking, Revolut, Spotify, Databricks) — almost always remote. Startups and agile teams — full-remote is the standard. Remote pay is often higher thanks to the international candidate pool. Few Junior remote openings exist — learning on live data is difficult without in-office mentorship.
How is a Data Engineer different from Data Scientist and Data Analyst?
A Data Engineer builds the infrastructure: ETL pipelines, warehouses, data streams. The goal is to make data collected, clean, and available at the right moment. Stack: Python, SQL, Spark, Airflow, Kafka. A Data Scientist analyses data and builds models: statistics, ML, A/B tests. Stack: Python, scikit-learn, PyTorch, Jupyter. A Data Analyst answers business questions through dashboards and reports. Stack: SQL, Excel, Tableau, Power BI, Looker. By pay: Data Engineer usually pays the most (most technical), Data Scientist close behind, Analyst sits 30–40% lower. Career flow: often Analyst → Data Engineer, or Analyst → Data Scientist via 1–2 years of reskilling.
Which companies actively hire Data Engineers?
The top Data Engineer employers across CIS and Europe: Yandex, Sber, OZON — large product, fintech, and marketplaces with dozens of data positions. Yandex (search, Market, Cloud, Metrica), Sber and Tinkoff (banking core, anti-fraud), Wildberries and OZON (e-commerce analytics, recommendations), VK (social graph, recs, ads), Avito (classifieds), Kaspi.kz (fintech in Kazakhstan). On the international side — Booking, Revolut, Spotify, Databricks, Snowflake actively hire Senior level on remote with pay above the local market. Startups in the data niche (Airbyte, dbt Labs, Estuary) — a premium segment for Lead/Principal. The full list is in the "Top companies" section above.
Where to start to become a Data Engineer in 2026?
The optimal path is to master Python + SQL to advanced level (window functions, query optimisation, EXPLAIN), then add Apache Airflow (DAGs, sensors, executors) and at least one cloud data warehouse (BigQuery, Snowflake, or ClickHouse). A pet project that looks good in interviews: an ETL pipeline that collects data from a public API, loads it into a data warehouse, and builds a dashboard in Metabase or Superset. At Middle add Apache Spark (PySpark) for batch processing of large volumes and Apache Kafka for streaming. At Senior — dbt for transformations and architectural patterns (lambda/kappa, data mesh, lakehouse). Docker, Kubernetes, and Linux basics are required.
How many Data Engineer jobs are open across CIS and Europe?
As of the latest data refresh, the Zorky CRM sample contains 2380 active open Data Engineer positions across CIS and Eastern Europe. These are postings published in the last 90 days — companies actually hiring. Geography is distributed; the leaders are 🇵🇱 Poland, 🇺🇸 USA, 🇷🇺 Russia. Data is collected from 1000+ sources: vacancy Telegram channels (an exclusive stream, especially for data startups), specialised job sites (HH, Habr Career, Djinni, DOU, NoFluffJobs, JustJoin.it, Pracuj.pl), and career pages of major fintech and marketplaces. Duplicates are filtered by description and URL. Seasonality: hiring usually peaks in February–March and September–October.
Where do Data Engineers earn more — in Russia or in Europe?
In absolute USD, Europe is consistently higher: in Poland (Warsaw, Krakow) a Senior Data Engineer earns $5,500–9,500/mo; in Germany (Berlin) €5,500–9,000/mo; in Czechia (Prague) €5,000–8,000. In Russia — Moscow Senior $4,500–8,000/mo, regions $3,000–6,000/mo. The main driver of the gap is contract currency and company type. International remote roles (Booking, Revolut, Spotify, Databricks, Snowflake) pay $7,000–12,000 for Senior regardless of country of residence. Local Russian banks (Sber, Tinkoff) on rouble contracts have closed the gap to the Polish market for Senior over 2 years. Kazakhstan (Almaty, Astana) is a growing hub at $3,000–6,000. Georgia attracts many remote relocants.
What skills does a Senior Data Engineer need?
A Senior Data Engineer owns the full data-infrastructure stack. Baseline: Python (advanced, async, optimisation), SQL (window functions, optimisation, plan reading), one cloud (AWS S3/EMR, GCP BigQuery/Dataflow, Azure Data Lake). Orchestration: Apache Airflow or Dagster (DAGs, sensors, custom operators). Distributed processing: Apache Spark (PySpark, optimisation, Catalyst). Streaming: Apache Kafka (producers, consumers, connectors). Warehouses: one of Snowflake, BigQuery, ClickHouse, Redshift. Transformations: dbt. Architectural patterns: lambda/kappa, data mesh, data lakehouse, slowly changing dimensions. Cross-cutting: Docker, Kubernetes, observability (Datadog, Prometheus), CI/CD.
Similar specializations
Methodology
- Data period: in the hero and copy — the last 3 months. In the charts — the full available observation period (since parsers were launched, usually 2-3 months).
- Data is collected automatically from 1000+ sources — Telegram channels and job boards across CIS and Europe.
- Only live open jobs with a clear description are counted. Spam and duplicates are filtered out.
- Salaries are converted to USD/month at the current rate. Outlier values (lt;500 or gt;50K) are filtered out.
- Levels are normalized: Mid → Middle, Intern/Trainee → Junior, Principal/Staff/Expert → Lead.
- The first 2 weeks of data (parser ramp-up period) are not shown in the charts.
- Data is recomputed every day.
Authorship and citation
Analytics prepared by Zorky Research Team. Last updated: May 29, 2026 at 9:06 PM.
Data sources and methodology
Data is collected automatically from 1000+ sources — Telegram job channels and job boards across CIS and Eastern Europe (HH, Habr Career, Djinni, DOU, NoFluffJobs, JustJoin.it, Pracuj.pl and others). Parsing runs 24/7, duplicates are filtered by description and URL, salary outliers are stripped. Detailed methodology — on the "How it works" page.
Zorky CRM (2026). Data Engineering in IT: CIS and Europe market. Accessed: 5/29/2026. URL: https://zorky.tech/en/research/data