Data Engineer with Databricks

Tech stack:

• SQL 
• Excel 
• Python 
• Microsoft Azure 
• Azure Blob Storage 
• Databricks 
• Power Apps 
• Power BI 

Codzienne zadania

• Transform unstructured and semi-structured R&D data into standardized, governed, and analytics-ready data assets. 
• Design, build, and operate scalable ETL/ELT pipelines, data lakes, and data warehouses with strong data quality, monitoring, and lineage. 
• Modernize legacy data flows through APIs and integration patterns within the Microsoft Azure ecosystem (e.g., Databricks, Blob Storage). 
• Optimize cloud infrastructure for performance, security, and cost efficiency while supporting enterprise data governance and compliance. 
• Partner with Data Scientists, Analysts, R&D scientists, IT teams, and vendors to enable ML/AI use cases and smart laboratory initiatives. 
• Identify siloed data sources and propose strategies to extract value through connectivity 
• Collaborate with cross-functional teams to design, implement, and maintain web applications using the newly structured data. 
• Contribute to Innovation Excellence standards, reusable components, and technical knowledge sharing across the whole company. 

Must have

• Data engineering
• SQL
• Excel
• Python
• Apache Spark
• Microsoft Azure
• Databricks
• Power BI
• ETL
• Data Lake
• Data warehouses
• Blob Storage
• AI