Data Engineer (Databricks) | Enterprise Energy Data Platform

Polcode is a Poland-based software house working with clients worldwide since 2006. They build web, mobile, and eCommerce products for startups and well-established companies across Europe, the US, and beyond. The company is a global, people-first software house with a team of almost 100 professionals helping build and improve digital businesses, software platforms, eCommerce stores, websites, and apps.

• Several years of commercial Data Engineering experience
• Hands-on commercial experience with Databricks
• Solid Python and SQL skills
• Experience with data modelling and ETL/ELT processes
• Experience building and orchestrating data pipelines
• Strong understanding of Data Lake and modern data platform concepts
• Understanding of layered data models such as Medallion Architecture (Bronze / Silver / Gold)
• Experience with permissions and access concepts
• Knowledge of continuous ingestion and continuous development practices
• Understanding of deployment processes and data quality practices
• Solution-oriented and structured approach to engineering challenges
• Strong communication skills and ability to work independently with stakeholders
• Experience working in agile projects, particularly Scrum
• Understanding of IT Service Management processes such as ITIL
• English sufficient to work effectively in an international environment

Nice to have:

• Experience with Microsoft Azure in a Databricks / Data Engineering environment
• Experience with Spark or PySpark
• Experience with streaming, CDC, Auto Loader, Structured Streaming, or similar continuous ingestion approaches
• Experience with Machine Learning or LLM solutions in Databricks
• Experience with Jira and Confluence
• Good German language skills

• Design and develop scalable data solutions in Databricks
• Integrate data into an enterprise Data Lake using a Medallion Architecture
• Build and maintain data models supporting reporting
• Develop and orchestrate ETL/ELT processes and data pipelines
• Work with Python and SQL on data transformation and processing
• Support continuous data ingestion and development processes
• Contribute to permissions and access concepts
• Work within multi-tier deployment environments and Quality Gates
• Optimize data processes for better performance, efficiency, and quality
• Document architectural decisions, processes, and project outcomes
• Collaborate with stakeholders in an agile environment