Senior Data Engineer

Data Engineering Strategy and Architecture:

• Design and implement scalable, reliable, and efficient data pipelines to support clinical, operational, and business needs.
• Develop and maintain architecture standards, reusable frameworks, and best practices across data engineering workflows.
• Build automated systems for data ingestion, transformation, and orchestration leveraging cloud-native and open-source tools.

Data Infrastructure and Performance Optimization:

• Optimize data storage and processing in data lakes and cloud data warehouses (Azure, Databricks).
• Develop and monitor batch and streaming data processes to ensure data accuracy, consistency, and timeliness.
• Maintain documentation and lineage tracking across datasets and pipelines to support transparency and governance.

Technology and Tools:

• Use Databricks, DBT, Azure Data Factory, and SQL to architect and deploy robust data engineering solutions.
• Integrate APIs, structured/unstructured data sources, and third-party systems into centralized data platforms.
• Evaluate and implement new technologies to enhance the scalability, observability, and automation of data operations.