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
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
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