Data Engineer
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Data Engineer
Stanowisko: Data Engineer
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About the Position
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What Sets Us Apart? Why Choose Us?
Collaborate with SmartWays – Spread Your Wings
What You Gain by Partnering with Us
- Partner relationships
- Knowledge and experience exchange
- Reports needed to make business decisions
- Listening to your needs
20+ people
in the team
6 years
of market experience
3000
satisfied clients
Who is a Data Engineer and What Do They Do?
A Data Engineer is a specialist responsible for designing, building, and maintaining data pipelines and infrastructure that feed analytics, reporting, and ML models with raw and processed data.
In the Polish market, the demand for this role is growing faster than for classical analysts – companies are migrating from spreadsheets and single databases to cloud architectures (Snowflake, BigQuery, Databricks) and data lakehouse approaches. In practice, this means that recruiting a data engineer is one of the most challenging IT processes: a candidate must combine programming skills, advanced SQL knowledge, and an understanding of data modeling. Headhunting a mid-level data engineer often involves searching for individuals with 3-5 years of experience who independently manage ETL/ELT processes and task orchestration.
Key Responsibilities of a Data Engineer
A mid-level data engineer works autonomously on a part of the data platform, collaborating with analysts, data scientists, and product teams. The scope of tasks includes:
- Designing and maintaining ETL/ELT pipelines that process data from source systems (transactional databases, APIs, files, event streams).
- Building and optimizing data warehouses and modeling layers (e.g., dbt, staging/marts layer).
- Orchestrating tasks using Apache Airflow, Dagster, or Prefect along with monitoring and alerting.
- Optimizing SQL queries and processing costs in cloud environments (partitioning, clustering, materializations).
- Implementing data quality control mechanisms (data quality tests, validations, data contracts).
- Integrating and processing real-time data using Kafka or Kinesis.
- Automating CI/CD processes for data processing code and infrastructure (Terraform, GitHub Actions).
- Documenting schemas, data lineage, and maintaining a data catalog.
- Collaborating with BI/DS teams to define requirements and model analytical layers.
- Ensuring data security and compliance (GDPR, access control, masking sensitive data).
Required Skills and Experience
The skill set of a mid-level data engineer is a technical foundation in SQL and Python, complemented by knowledge of at least one cloud platform and orchestration tools. The table below presents typical requirements in recruitments at this level:
| Skill | Required Level | Details |
|---|---|---|
| SQL | Advanced | Window functions, CTE, query optimization, dimensional modeling. |
| Python | Intermediate | Data processing (pandas/PySpark), writing ETL scripts, unit tests. |
| Cloud (GCP/AWS/Azure) | Practical | BigQuery, Snowflake, Databricks, or Redshift – at least one production platform. |
| Orchestration | Practical | Apache Airflow (DAGs, sensors) or Dagster/Prefect. |
| Data Modeling | Intermediate | dbt, staging/intermediate/marts layers, star schema. |
| Big Data | Basic/Intermediate | Apache Spark, distributed processing, job optimization. |
| Streaming | Highly desirable | Kafka, Kinesis, near-real-time event processing. |
| DevOps/IaC | Basic | Git, CI/CD, Docker, Terraform. |
| Experience | 3-5 years | Independently managing production pipelines. |
| English | B2+ | Technical documentation, working in international teams. |
Salary and Market Ranges for 2026
A mid-level data engineer earns 15,000–24,000 PLN gross/month on an employment contract in 2026, and on a B2B contract, rates reach 130–180 PLN/h net+VAT. Several factors influence the salary:
- Location – Warsaw and Kraków offer 10-15% more than smaller centers; remote work equalizes differences.
- Industry – Fintech, e-commerce, and product companies pay more than software houses.
- Tech Stack – Experience with Databricks, Snowflake, or streaming raises the range by 2000-4000 PLN.
- Certifications – Google Cloud Professional Data Engineer, AWS Data Analytics, or Databricks Certified increase candidate attractiveness.
- Experience – Closer to 5 years and architectural independence is the upper limit of the range.
The standard benefits package includes private healthcare, a training budget of 3000-6000 PLN annually, a sports pass, flexible hours, and a remote or hybrid work model. In product companies, annual bonuses and funded certification exams in the cloud are common.
How Does Hiring a Data Engineer Work with Smartways.io
Hiring a data engineer with Smartways.io is based on a success fee model and a structured process that reduces the time to offer submission. The stages are as follows:
- Needs Analysis and Briefing (1-2 days) – We determine the tech stack, seniority level, work mode, salary range, and the ideal candidate profile.
- Direct Search and Pre-selection (5-8 days) – Active headhunting of data engineers in a database of over 100,000+ IT specialists and technical CV verification.
- Competency Interviews (3-5 days) – Assessment of SQL, Python, cloud experience, and cultural fit.
- Shortlist Presentation (2-3 days) – We provide 3-5 verified profiles with recommendations and financial expectations.
- Support in Finalization (3-4 days) – Coordination of final interviews, offer negotiation, and onboarding.
The entire process typically takes 3-4 weeks from briefing to signing the contract. You pay only for the successfully hired candidate, and each recruitment is covered by a recruitment guarantee in case of the specialist leaving early.
FAQ – Common Questions About the Data Engineer Position
How Much Does It Cost to Recruit a Data Engineer with Smartways.io?
We charge on a success fee model – the fee is calculated only after hiring the candidate and is a percentage of their annual salary. We do not charge upfront fees or a subscription for the search process.
How Does a Data Engineer Differ from a Data Scientist and Data Analyst?
A data engineer builds and maintains data infrastructure and pipelines, a data analyst interprets data and creates reports, and a data scientist builds predictive and ML models. A data engineer is the foundation without which the other roles do not have access to reliable data.
How Long Does It Take to Find a Mid-Level Data Engineer?
Standardly 3-4 weeks from briefing to offer submission. With a very narrow tech stack (e.g., required production experience with streaming and Databricks), the process may extend to 5-6 weeks.
Can a Data Engineer Work Fully Remotely?
Yes – most offers for this position allow for remote or hybrid work. The work focuses on code, cloud, and data pipelines, which works well in a distributed model.
What Technologies Should Be Verified During the Recruitment of a Data Engineer?
Priority technologies are SQL (advanced), Python, one cloud platform (BigQuery/Snowflake/Databricks), and orchestration in Airflow. Additionally, it is worth checking knowledge of dbt, Spark, and basic IaC.
Does Smartways.io Recruit Other Technical and Product Roles?
Yes, we also recruit for positions such as senior product manager, Angular developer, or React Native developer, which facilitates building complete product-technical teams with a single recruitment partner.
Hire a Data Engineer
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Stanowisko: Data Engineer
Możemy w krótkim czasie przesłać Ci dobrych kandydatów. Skontaktuj się z nami
SmartWays Sp. z o.o. - 2026 - All rights reserved.
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About the Company SmartWays Recruitment offers bespoke and scalable recruitment solutions tailored to the evolving needs of businesses across various industries. The company focuses on recruitment within EMEA markets but delivers projects globally. Their services include direct search, contracting, body leasing, executive search, recruitment process outsourcing, and HR on-demand services. Products, Services & Tech Stack Core Solutions: Direct Search Contracting Body Leasing Executive Search Recruitment Process Outsourcing HR on-demand Project Scope & Target Clients Client Base: IT Finance Sales Purchasing Other industries Engineering Scale: Projects for large corporations, small businesses, and start-ups.