Data Engineer- PySpark & Python

Hirexa Solutions; Kraków; On-site; PLN 180,000 - 320,000; Full time

Job summary

Hirexa Solutions in Kraków is seeking experienced Data Engineers to design, develop, and optimize scalable data pipelines using PySpark and Python. You will build ETL/ELT workflows for large-scale environments and collaborate with data science, analytics, and architecture teams.

Experience with Azure Data Factory is required, with Azure Databricks as a plus. The role emphasizes performance tuning, data quality, and end-to-end data processing excellence in a modern cloud data stack.

Qualifications

• 6–10 years of overall IT experience.
• 4–5 years hands-on PySpark and Python development.
• Strong data engineering principles and modern pipeline architectures.
• Proficiency in PySpark (Spark SQL, DataFrames, performance tuning).
• Python scripting and application development.
• Experience with Azure Data Factory orchestration and pipeline development.
• Knowledge of data optimization techniques: partitioning, caching, joins, query optimization.
• Experience with large-scale distributed data processing systems.
• Strong analytical and problem-solving skills.
• Good understanding of SQL, databases, and data modeling.

Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark and Python.
• Build and optimize ETL/ELT workflows for processing large volumes of data.
• Write efficient, reusable, and high-performance code with a strong focus on optimization.
• Process and manage structured and unstructured data from multiple sources.
• Implement best practices related to data engineering, performance tuning, and code quality.
• Develop, orchestrate, and monitor data workflows using Azure Data Factory (ADF).
• Collaborate with Data Scientists, Data Analysts, Solution Architects, and other stakeholders.
• Ensure data quality, reliability, and integrity across all data platforms.
• Troubleshoot and resolve performance bottlenecks in data processing pipelines.
• Contribute to data architecture discussions and continuous improvement initiatives.

Skills

PySpark

Python

SQL

Data engineering

Performance optimization

Tools

Azure Data Factory

Azure Databricks

Spark SQL

Job description

We are seeking experienced Data Engineers with strong expertise in PySpark and Python to join our growing data engineering team in Kraków. The successful candidates will be responsible for designing, developing, and optimizing scalable data pipelines and data processing solutions for large-scale enterprise environments.

Experience with Azure Data Factory (ADF) is required, while hands-on experience with Azure Databricks (ADB) will be considered a significant advantage.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark and Python.
• Build and optimize ETL/ELT workflows for processing large volumes of data.
• Write efficient, reusable, and high-performance code with a strong focus on optimization.
• Process and manage structured and unstructured data from multiple sources.
• Implement best practices related to data engineering, performance tuning, and code quality.
• Develop, orchestrate, and monitor data workflows using Azure Data Factory (ADF).
• Collaborate with Data Scientists, Data Analysts, Solution Architects, and other stakeholders.
• Ensure data quality, reliability, and integrity across all data platforms.
• Troubleshoot and resolve performance bottlenecks in data processing pipelines.
• Contribute to data architecture discussions and continuous improvement initiatives.

Required Skills & Experience

• 6–10 years of overall IT experience.
• 4–5 years of hands-on experience in PySpark and Python development.
• Strong understanding of data engineering principles and modern data pipeline architectures.
• PySpark (Spark SQL, DataFrames, performance tuning)
• Python scripting and application development
• Azure Data Factory (ADF) orchestration and pipeline development
• Strong knowledge of data optimization techniques, including partitioning, caching, joins, and query optimization.
• Experience working with large-scale distributed data processing systems.
• Strong analytical and problem-solving skills.
• Good understanding of SQL, database concepts, and data modeling.

Nice-to-Have Skills:

• Hands-on experience with Azure Databricks (ADB).
• Exposure to cloud technologies, preferably Microsoft Azure.
• Experience with CI/CD pipelines and DevOps practices for data engineering.
• Knowledge of Data Lake and Lakehouse architectures.
• Familiarity with modern data governance and monitoring practices.