Senior BigData Engineer (Databricks + Azure)

Location: Ukraine; remote or office work

Company

Engineering and technology organization delivering data and analytics solutions.

What you will do

• Design, develop, and maintain scalable batch and streaming ETL pipelines on the Databricks Lakehouse platform.
• Build and optimize data processing solutions with PySpark, Python, and SQL.
• Configure Databricks clusters and SQL Warehouses and support data platform optimization.
• Implement Unity Catalog governance, including access control, lineage, and cross-workspace data sharing.
• Develop and deploy solutions with Databricks Asset Bundles and CI/CD processes.
• Design bronze–silver–gold Lakehouse architectures, expose data through Databricks SQL and Power BI, and contribute to architecture and continuous improvement initiatives.

Requirements

• 5+ years of experience in data engineering, including data modeling and scalable ETL pipeline design.
• Strong expertise in PySpark, Python, and SQL, including performance tuning and optimization.
• Hands-on experience with Databricks clusters, SQL Warehouses, Delta Lake, and Lakehouse architecture.
• Practical knowledge of Unity Catalog governance, fine-grained access control, lineage, and data sharing.
• Experience with Databricks Asset Bundles, CI/CD, Databricks SQL, and BI tools such as Power BI.
• Upper-intermediate or higher English and strong communication skills with technical and business stakeholders.

Nice to have

• Experience with Databricks AI/BI tools such as MLflow, Dashboards, Metric Views, Genie, or agents.
• Experience with Azure data services including ADF, Synapse, ADLS, Azure DevOps, or Microsoft Fabric.

Culture & Benefits

• Remote or office work format in Ukraine.
• Collaboration with technical and business stakeholders throughout the project lifecycle.
• Participation in architecture discussions and continuous improvement initiatives.