Python Data Engineer DataBricks
Summary
Data engineer (7-15 years' experience) building scalable ETL pipelines with Python and Databricks, integrating sources via REST APIs and delivering to Snowflake on Linux/cloud. Covers the full ETL lifecycle with testing, monitoring, documentation, code reviews, and agile delivery in an international team.
Build scalable ETL pipelines with Python and DataBricks in an international, collaborative setting focused on reliable data solutions. Work across teams to turn business requirements into efficient workflows and modern cloud data solutions.
This Data Engineer role suits professionals with 7-15 years of relevant experience. You will develop data workflows using Python, DataBricks, Snowflake, REST APIs, and Linux. The position includes agile delivery, software engineering practices, testing, monitoring, and documentation. You will contribute to reliable data engineering across the complete extraction, transformation, and loading lifecycle.
Key Responsibilities:
- Gather data requirements with cross-functional teams
- Develop scalable ETL processes using Python and DataBricks
- Manage pipelines, monitoring, error handling, and optimization
- Integrate data sources through REST APIs and related techniques
- Participate in agile ceremonies and conduct code reviews
Requirements:
- Strong Python proficiency and software engineering practices
- Hands-on DataBricks experience developing scalable data solutions
- Seven to fifteen years of relevant experience
- Snowflake or similar cloud data warehouse proficiency
- Understanding of ETL design, modeling, and warehousing
Apply Python, DataBricks, ETL, and cloud data warehouse expertise to engineer reliable, scalable workflows.