- Design, develop, and maintain scalable, production-ready data pipelines using Spark, Python, and SQL in a Databricks environment.
- Integrate and transform health, financial, and operational datasets into reusable data products.
- Develop data models and analytics datasets for enterprise reporting and operational decision-making.
- Build and maintain API-based integrations for ingesting and exchanging data across systems.
- Monitor, troubleshoot, and optimize scheduled workflows and production pipelines.
- Implement data validation, quality checks, lineage, and governance practices.
- Contribute to automated testing, code reviews, technical documentation, and reusable engineering patterns.
- Collaborate with engineers, architects, analysts, and customer stakeholders to translate data needs into technical solutions.
PythonSQLGit+4 more