Data Engineer

Data Engineer (PySpark & Python) Location Krakow, Poland (Hybrid) Contract B2B Contract Experience 6–10 Years Rate 1000–2000 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