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
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
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
