Senior Data Engineering Analyst
unitedhealthgroup
Job Description
- Data Engineering & Pipeline Development
- Design, develop, and maintain scalable data pipelines and ETL/ELT processes supporting batch and streaming workloads
- Build and optimize data ingestion frameworks using technologies such as Apache Spark, Kafka, and cloud-native services
- Integrate data from multiple internal and external source systems while ensuring data quality, consistency, and governance
- Develop and maintain data orchestration workflows to ensure reliable delivery of business-critical datasets
- Data Architecture & Modeling
- Design and optimize data warehouses, data lakes, and lakehouse architectures
- Build scalable and efficient data models supporting enterprise reporting, analytics, and AI/ML use cases
- Work with platforms such as Snowflake, Delta Lake, Apache Iceberg, and cloud-based data ecosystems
- Define and maintain data contracts, metadata standards, and lineage frameworks
- Data Security, Governance & Compliance
- Design secure and compliant data pipelines incorporating encryption, IAM, RBAC, audit logging, and access controls
- Implement data classification, masking, tokenization, and lineage solutions for sensitive healthcare data including PII and PHI
- Support adherence to HIPAA, HITRUST, SOC 2, and enterprise security requirements
- Contribute to audit readiness by maintaining controls documentation, access reviews, lineage records, and compliance evidence
- Data Reliability & Observability
- Own data quality, observability, monitoring, and reliability for assigned business domains
- Establish and monitor SLAs, data validation checks, and alerting mechanisms
- Troubleshoot production issues, optimize performance, and ensure platform stability
- Drive best practices around data testing, monitoring, and operational excellence
- Cloud & Platform Engineering
- Support and enhance modern cloud-based data platforms, with a strong preference for AWS technologies
- Implement CI/CD pipelines, Infrastructure as Code (IaC), and automated deployment practices
- Optimize infrastructure utilization through right-sizing, auto-scaling, partitioning, clustering, and cost-management strategies
- Contribute to platform automation and engineering process improvements
- Analytics & AI Enablement
- Collaborate with Analytics, BI, and Data Science teams to enable reporting, advanced analytics, machine learning, and AI solutions
- Develop feature stores and ML-ready datasets for predictive modeling initiatives
- Ensure data accessibility, consistency, and reliability for downstream analytical applications
- Documentation & Leadership
- Create and maintain technical documentation, architecture diagrams, schemas, and operational procedures
- Document end-to-end data lineage, governance frameworks, and engineering standards
- Mentor Associate and Junior Data Engineers, promoting engineering best practices and knowledge sharing
- Stay current with emerging technologies, cloud innovations, security standards, and modern data engineering methodologies
- Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements