Senior Data Engineering Analyst

UnitedHealth Group; Dadri; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

UnitedHealth Group is seeking a Data Engineer to design and optimize scalable data pipelines, ensuring quality and governance across data assets. You will work with Spark, Kafka, Snowflake, and cloud platforms to enable analytics and AI/ML initiatives.

You will collaborate with Analytics, BI, and Data Science teams, implement CI/CD and IaC practices, and mentor junior engineers while adhering to HIPAA-like security standards.

Qualifications

• Bachelor's or Master's degree in a relevant field.
• 4+ years of experience in Data Engineering or related areas.
• Hands-on with ETL/ELT pipelines and large-scale data processing.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Build data ingestion frameworks using Spark, Kafka, and cloud-native services.
• Design data warehouses, lakes, and lakehouse architectures for analytics.
• Ensure data governance, quality, and lineage across datasets.
• Collaborate with Analytics/BI/Data Science teams for AI/ML use cases.

Skills

Spark

Kafka

Python

SQL

ETL/ELT

Education

Bachelor's or Master's in CS/IT/Data Eng

Tools

Snowflake

Delta Lake

Iceberg

AWS

Terraform

Kubernetes

Docker

Job description

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Primary Responsibilities:

• 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

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, Engineering, or a related field
• 4+ years of experience in Data Engineering, Data Platform Engineering, or related areas
• Solid experience building and maintaining ETL/ELT pipelines and large-scale data processing systems
• Hands-on experience with Apache Spark and distributed data processing frameworks
• Experience working with Kafka or other streaming technologies
• Experience with Snowflake, Delta Lake, Apache Iceberg, or similar cloud data platforms
• Solid knowledge of data warehousing and lakehouse architectures
• Solid understanding of data governance, metadata management, and data lineage concepts
• Familiarity with CI/CD, Infrastructure as Code, and DevOps practices
• Proficiency in SQL and Python
• Proven excellent analytical, troubleshooting, and problem-solving skills
• Proven solid communication and stakeholder management capabilities

Preferred Qualifications:

• Hands-on experience with AWS services such as S3, Glue, EMR, Lambda, Redshift, IAM, KMS, and CloudWatch
• Experience implementing HIPAA, HITRUST, SOC2, or other regulated industry compliance requirements
• Experience supporting AI, Machine Learning, and Data Science workloads
• Experience with Terraform, Kubernetes, Docker, and modern cloud-native architectures
• Knowledge of data security practices including encryption, tokenization, data masking, and access management
• Familiarity with feature stores, MLOps, and ML data pipelines
• Proven exposure to vulnerability management tools such as Snyk, Wiz, Trivy, or equivalent

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.