Key skills
PySparkSQLDatabricksHealthcare domain knowledgeMedallion architectureData quality frameworksSpark optimizationCloud environmentsCI/CDVersion controlDevOps practicesAnalytical skillsETLData EngineeringSparkAzureVersion ControlCachingCommunication
About this role
Cognizant is seeking a highly skilled Senior Data Engineer with expertise in PySpark, SQL, and Databricks to support the design and development of large-scale data pipelines. The role involves building scalable data pipelines, implementing data quality frameworks, and ensuring compliance with healthcare data standards.
Responsibilities:
- Design, build, and maintain scalable data pipelines using PySpark based ETL, SQL, and Databricks
- Implement and enhance medallion architecture (Bronze/Silver/Gold) for structured, governed data delivery
- Develop and enforce data quality frameworks, validation rules, and monitoring processes
- Optimize Spark jobs for performance, reliability, and cost efficiency
- Collaborate with cross‑functional teams including data architects, analysts, and business stakeholders
- Translate healthcare business requirements into robust technical solutions
- Ensure compliance with healthcare data standards, privacy regulations, and governance practices
- Claims ingestion and orchestration
- Data validation and transformation
- Supporting batch and event-driven workflows
- Feature engineering
Requirements:
- Strong hands‑on experience with PySpark based ETL, SQL, and Databricks
- Deep understanding of medallion architecture and modern data lakehouse patterns
- Experience implementing data quality frameworks and automated validation
- Proficiency in Spark optimization techniques (partitioning, caching, AQE, cluster tuning)
- Familiarity with CI/CD, version control, and DevOps practices for data engineering
- Experience working with healthcare claims platforms such as Facets, QNXT, or Health Rules
- Understanding of CPT, ICD‑10, HCPCS, and related healthcare coding standards
- Knowledge of claims lifecycle, adjudication processes, and provider/member data structures
- Ability to interpret healthcare data models and ensure accurate mapping, transformation, and enrichment
- Experience in cloud environments (Azure preferred)
- Exposure to data governance, MDM, and metadata management
- Strong analytical, communication, and problem‑solving skills
- Ability to work independently and drive technical decisions