Data Engineer - Hybrid from Krakow

Data Engineer

We are seeking a highly experienced Data Engineer on behalf of our client — a leader within one of the largest Swiss financial holding companies.

📍 Work mode: Hybrid — 3 days a week onsite at the client’s office in Kraków.

🔹 Experience Requirements

• 5–10 years of hands-on experience in data analytics as a Data Engineer. Familiarity with ETL, DQ, DM, and reject/recycling concepts.

• Proven experience in building data analytics solutions within big data environments (Hadoop clusters or cloud-based).

🔹 Core Skills

Primary: PySpark, Python

Secondary: Databricks, Airflow, Azure

Good to have: Experience with CI/CD pipelines and Agile methodologies

Technical Expertise

• Extensive experience in building data pipelines using Spark (especially PySpark).

• Minimum 3 years of hands-on PySpark coding (using RDDs, DataFrames & Datasets — not only Spark SQL).

• Proven experience developing multiple Spark applications for large-scale data processing.

• Strong performance tuning and complex transformation skills (grouping, window functions, etc.).

• Participation in PySpark code hackathons is a plus.

• Must be confident writing clean, efficient, and reusable PySpark & Python code during interviews.

• Skilled in troubleshooting, automation scripting, and maintaining code quality.

- This role requires advanced Python coding skills — not just basic or theoretical knowledge. You will be asked to demonstrate your Python expertise during the interview.

Additional Skills

• Excellent problem-solving and analytical abilities.

• Strong understanding of business requirements and ability to translate them into technical solutions.

• Effective communication and team collaboration skills.

• Experience across the software development lifecycle, including CI/CD.

• Comfortable working in an Agile environment.

📩 If you’re interested and meet the qualifications, please send your CV to Alina Pchelnikova at alina.pchelnikova@dcvtechnologies.co.uk