Data Engineer

Data Engineer (PySpark & Python)

Location

Krakow, Poland (Hybrid)

Contract

B2B Contract

Experience

6–10 Years

Rate

1200–1550 PLN/day

Role Overview

We are seeking experienced Data Engineers to design, build, and optimize large-scale data processing solutions within a global banking environment.

The role focuses on PySpark, Python, Azure Data Factory, and distributed data processing platforms, with a strong emphasis on performance optimization, scalability, and data engineering best practices.

Key Responsibilities

• Design and develop scalable data pipelines using PySpark and Python

• Build and optimize ETL/ELT workflows

• Develop high-performance data processing solutions

• Work with structured and unstructured datasets

• Implement data engineering best practices

• Develop and orchestrate pipelines using Azure Data Factory (ADF)

• Optimize Spark jobs and distributed processing workloads

• Collaborate with Data Scientists, Architects, and Analysts

• Ensure data quality, reliability, and performance

• Troubleshoot data processing bottlenecks

Must Have Skills

• PySpark

• Python

• Azure Data Factory (ADF)

• Spark SQL

• DataFrames

• ETL / ELT Development

• Data Pipeline Design

• SQL

• Data Modelling

• Performance Tuning

• Distributed Data Processing

Nice to Have

• Azure Databricks

• Microsoft Azure

• CI/CD Pipelines

• Data Lake / Lakehouse Architectures

Ideal Background

• Data Engineer

• Big Data Engineer

• Azure Data Engineer

• Spark Engineer

• PySpark Engineer

• ETL Engineer