AIA - Weekend Drive - BBSR 04th July 2026 Interview Location: Bhubaneswar Mode Of Interview : Face to Face Interview Date: 04th July 2026 Skill: Azure Databricks & Pyspark Experience - 6 - 9 Years
Job Summary
This hybrid Data Engineer role focuses on designing and optimizing Databricks SQL and PySpark solutions for complex payer and Medicare Medicaid claims processing. The role spans data engineering analytics and quality assurance to ensure accurate claim insights that support compliant healthcare decisions and improved member outcomes.
Responsibilities
Data Engineering - Pyspark Data bricks
Design scalable Databricks SQL and PySpark solutions that process large volumes of payer and Medicare Medicaid claims data to ensure reliable analytics outputs
Develop robust data pipelines that ingest transform and aggregate claims information to support timely decision making for healthcare operations
Optimize PySpark jobs and Databricks SQL queries to improve runtime performance stability and cost efficiency across the hybrid cloud environment
Implement reusable data models and curated datasets tailored for claims adjudication analytics risk scoring and operational reporting needs
Collaborate with business and product stakeholders to translate payer and claims requirements into detailed technical solutions that align with organizational goals
Perform detailed data profiling and validation on Medicare Medicaid claims to identify anomalies gaps and quality issues before downstream consumption
Create automated testing frameworks for Databricks SQL and PySpark components to reduce defects and maintain consistent quality across releases
Document end to end data flows transformation logic and technical design decisions to ensure transparency maintainability and effective knowledge sharing
Partner with analysts and data consumers to design efficient query patterns and dashboards that reveal actionable insights from claims trends and utilization metrics
Ensure compliance with healthcare data policies by implementing appropriate access controls masking strategies and audit trails within the Databricks environment
Troubleshoot production issues in Databricks jobs by analyzing logs dependencies and datasets to restore service with minimal impact to downstream users
Coordinate with infrastructure and platform teams to align cluster configurations libraries and deployment processes with performance and reliability requirements
Contribute to continuous improvement by recommending new Databricks features coding patterns and automation approaches that enhance team productivity and solution quality
Qualifications
Exhibit advanced proficiency in Databricks SQL by crafting complex joins aggregations and window functions that support nuanced payer and claims analytic scenarios
Demonstrate strong PySpark experience through hands on development of distributed data processing pipelines capable of handling large scale Medicare Medicaid claims datasets
Apply deep understanding of payer operations and claims life cycle to design transformations that respect benefit rules payment logic and regulatory constraints
Utilize practical knowledge of Medicare and Medicaid programs to ensure that analytic outputs support compliance reporting and value based care initiatives
Bring eight to twelve years of professional experience in data engineering or advanced analytics roles with a focus on enterprise scale implementations
Communicate effectively in hybrid work settings by coordinating work progress clarifications and issue resolutions with onsite and remote stakeholders during day shifts
Adopt structured development practices including version control code reviews and documentation to improve reliability and long term maintainability of solutions
