Senior Databricks Data Engineer

We are looking for a Senior Databricks Data Engineer with strong expertise in Databricks, cloud data architecture, data engineering, and healthcare data. The ideal candidate will be responsible for designing scalable, secure, and high-performance data platforms supporting healthcare analytics and data integration.

The candidate should have strong knowledge of modern data architecture, Lakehouse architecture, SQL, Python, data governance, and healthcare domain workflows.

• Design and lead Databricks Lakehouse architecture for large-scale healthcare data platforms.


• Define scalable data architectures for batch and real-time healthcare data processing.


• Design data ingestion, transformation, storage, and consumption patterns using Databricks.


• Develop architecture using Delta Lake, Unity Catalog, Databricks Workflows, and Delta Live Tables/Lakeflow.


• Integrate data from multiple healthcare sources, including clinical, claims, eligibility, provider, and patient systems.


• Design robust ETL/ELT pipelines using PySpark, SQL, and Databricks.


• Establish data quality, validation, reconciliation, lineage, and governance frameworks.


• Design secure healthcare data solutions while considering HIPAA and PHI/PII protection requirements.


• Work with cloud platforms such as Azure, AWS, or GCP to build scalable data solutions.


• Collaborate with data engineers, data scientists, analysts, product owners, and business stakeholders.


• Define technical standards, architectural patterns, and best practices for Databricks development.


• Lead performance optimization and cost-management initiatives across the Databricks platform.


• Provide technical leadership and mentoring to data engineering teams.


• Participate in Agile ceremonies and contribute to technical planning and roadmap discussions.

• Strong hands-on experience with Databricks.


• Expertise in Lakehouse architecture and Delta Lake.


• Strong PySpark and SQL skills.


• Experience with Unity Catalog and data governance.


• Experience designing enterprise-scale data platforms.


• Strong knowledge of ETL/ELT and data modeling.


• Experience with cloud platforms such as Azure, AWS, or GCP.


• Experience with data integration and orchestration tools.


• Knowledge of CI/CD, Git, and DevOps practices.


• Strong understanding of data security and access control.


• Experience with Agile/Scrum methodologies.