Senior Data Engineer

Quick Facts

• Remote work
• B2B rate: 135–150 PLN net

Description

Design and implement ETL/ELT data architecture in Databricks. Build and optimize scalable data pipelines using Apache Spark and Python/Scala, while automating processing and ensuring performance and scalability. Monitor, diagnose, and resolve performance issues in data environments, supporting data quality, security, and metadata management practices.

Responsibilities

• Design and implement ETL/ELT architecture in Databricks
• Create and optimize data pipelines with Apache Spark and Python/Scala
• Collaborate with analytics and product teams to translate business requirements into technical solutions
• Automate data processing and ensure performance and scalability
• Monitor, diagnose, and troubleshoot data environment performance issues
• Implement data quality, security, and metadata management practices
• Create technical documentation and participate in code reviews

Requirements

• 3–5 years of experience with large-scale data processing and Spark/Databricks platforms
• Advanced Python or Scala, with ability to write efficient queries and data transformations
• Experience designing and deploying ETL/ELT pipelines and working with data warehouses and data lakes
• Knowledge of Spark performance optimization, resource management, and cluster tuning
• Experience with version control using Git and CI/CD tooling for data solutions
• Strong communication skills and cross-team collaboration experience
• Technical higher education or equivalent professional experience in data engineering

Benefits

• Remote work
• 135–150 PLN net on B2B