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
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
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