Data Engineer
⚲ Kraków
Do uzgodnienia
Wymagania
- PySpark Python
- Azure Data Factory (ADF)
- Spark SQL DataFrames
- DataFrames ETL / ELT Developmen
- SQL Data Modelling
- Performance Tuning Distributed Data Processing
Opis stanowiska
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
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
🔍 Dekoder Ogłoszenia
🔴
design, build, and optimize large-scale data processing solutions within a global banking environment
Może oznaczać pracę nad bardzo złożonymi, ale też potencjalnie przestarzałymi systemami w dużej, biurokratycznej organizacji.
🔴
strong emphasis on performance optimization, scalability, and data engineering best practices
Może sugerować, że obecne rozwiązania są dalekie od optymalnych i wymagają gruntownych zmian, co może być czasochłonne.
🔴
Troubleshoot data processing bottlenecks
Może oznaczać, że będziesz głównie naprawiać istniejące problemy, a nie budować nowe, innowacyjne rozwiązania.
🟡
Collaborate with Data Scientists, Architects, and Analysts
Współpraca może oznaczać konieczność negocjowania i przekonywania innych zespołów do swoich rozwiązań, co może być czasochłonne.
🟡
Ideal Background: Data Engineer, Big Data Engineer, Azure Data Engineer, Spark Engineer, PySpark Engineer, ETL Engineer
Szeroki zakres idealnych kandydatów sugeruje, że firma może nie mieć jasno sprecyzowanych oczekiwań co do konkretnego profilu, a rola może być elastyczna.