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
Responsibilities
- Design and develop scalable data pipelines using Databricks SQL and PySpark to process high volume Medicare and Medicaid claims data across payer systems
- Implement efficient data models that support analytics use cases for claims adjudication trends member insights and provider performance improvement
- Optimize PySpark jobs and Databricks SQL queries to ensure reliable performance cost efficiency and predictable runtime for large claims datasets
- Build reusable data transformation frameworks that standardize ingest cleanse enrich and aggregate payer claims information from multiple source systems
- Collaborate with product owners business analysts and data consumers to translate Medicare and Medicaid payer requirements into robust technical data solutions
- Ensure data quality by implementing validation rules reconciliation checks and anomaly detection tailored to claims and payer domain constraints
- Develop secure data handling practices that protect member privacy and comply with healthcare regulations while enabling responsible analytics on claims data
- Create robust monitoring logging and alerting for Databricks workloads to proactively identify failures bottlenecks and data quality issues in production pipelines
- Document end to end data flows technical designs and operational runbooks so that hybrid teams can support and enhance Databricks and PySpark solutions effectively
- Work closely with testing and operations partners to support deployments defect triage and continuous improvements for production claims analytics platforms
- Partner with business stakeholders to deliver dashboards curated datasets and self service views that enable timely insights on claims cost quality and utilization outcomes
- Contribute to continuous improvement by evaluating new Databricks features PySpark capabilities and engineering practices that enhance stability maintainability and scalability
- Mentor peers through code reviews design discussions and knowledge sharing sessions to uplift engineering standards across data and analytics teams
Qualifications
- Possess a strong background in Databricks SQL with hands on experience writing complex queries optimizing execution plans and managing large scale tables in production
- Demonstrate advanced proficiency in PySpark including structured streaming dataframes and performance tuning techniques applicable to healthcare claims processing
- Bring deep domain understanding of Medicare and Medicaid claims payer operations and healthcare reimbursement workflows enabling accurate translation of business rules into code
- Apply solid knowledge of data warehousing concepts such as star schemas slowly changing dimensions and partitioning to support analytics on claims data
- Exhibit strong skills in debugging troubleshooting and root cause analysis for distributed data processing jobs within cloud based Databricks environments
- Show experience in working within hybrid work models using modern collaboration tools and following agile delivery practices for data engineering initiatives
- Display familiarity with healthcare data standards coding systems and regulatory expectations that influence design of claims analytics and reporting solutions
- Utilize effective communication and stakeholder engagement skills to align technical deliverables with business outcomes focused on member health and payer efficiency
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
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