Senior Data Engineer

This position is within the Sustainability Data & AI team working to build and operate a modern Sustainability Data Foundation based on Databricks in the pharmaceutical industry.

• 5+ years of experience in data engineering and data platforms.
• Strong production experience with Databricks.
• Expert knowledge of PySpark, SQL, data modelling, and data pipeline design.
• Experience with CI/CD, Git, automated testing, and deployment.
• Knowledge of data quality, governance, lineage, and auditing.
• Strong troubleshooting and root-cause analysis skills.
• Ability to take ownership and deliver pragmatic, production-ready solutions.

Nice to have:

• Experience with ESG / sustainability or regulatory reporting.
• Knowledge of ERP, procurement, finance, or supplier data.
• Experience building Databricks applications, dashboards, or user-facing tools.

• Design and develop data pipelines and data products using Databricks, Delta Lake, and PySpark.
• Build data models and transformation frameworks for large and complex datasets.
• Develop data quality controls, validation, and reconciliation processes.
• Optimize pipelines for performance, scalability, and cost.
• Implement CI/CD, automated testing, and deployment processes.
• Support data governance, lineage, security, and access management.
• Collaborate with Sustainability, Business, Product, and Reporting teams.
• Troubleshoot issues, perform root-cause analysis, and ensure reliable production delivery.
• Develop Databricks-based tools to simplify data access and reporting.