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
Design, develop, test, and deploy scalable data pipelines using Azure Databricks, Spark SQL, Python, and Airflow
Build and maintain data ingestion, transformation, and data curation processes across multiple enterprise data sources
Develop complex SQL queries and optimize data processing workflows for performance and scalability
Create, maintain, and support Airflow DAGs for orchestration, scheduling, monitoring, and error handling
Collaborate with Product Owners, Business Analysts, and stakeholders during requirements gathering, backlog refinement, and sprint planning activities
Implement data quality validations, reconciliation checks, and exception handling mechanisms
Support the development and maintenance of Delta Lake and Lakehouse architectures within Databricks
Participate in data platform modernization and cloud migration initiatives
Develop reusable frameworks, utilities, and automation solutions to improve engineering efficiency
Troubleshoot pipeline failures, performance bottlenecks, and complex data issues
Follow coding standards, security requirements, and engineering best practices
Contribute to CI/CD implementation and automated deployment processes
Work closely with cross-functional teams to support analytics, reporting, AI, and business operational needs
Prepare and maintain technical documentation, design specifications, and operational runbooks
Support production deployments, incident resolution, root cause analysis, and operational excellence initiatives
Utilize AI-assisted development tools and automation capabilities to improve delivery efficiency and code quality
Provide technical recommendations and participate in design reviews and architecture discussions
Demonstrate ownership, accountability, and commitment to project deliverables
Stay current with emerging technologies, cloud services, and modern data engineering practices
Comply with company policies, security standards, and organizational guidelines
Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Required Qualifications
Bachelor's Degree in Engineering, Computer Science, Information Technology, MCA, or equivalent experience
4+ years of relevant hands-on experience in Azure Databricks and Modern Data Engineering
Experience working in Agile/Scrum delivery environments
Technical Skills
Data Engineering Expertise
- Data ingestion frameworks
- Data transformation and enrichment
- Batch processing pipelines
- Data quality implementation
- Query optimization
- Performance tuning
- Metadata and lineage concepts
- Cloud Technologies knowledge
Microsoft Azure
Azure Data Factory (ADF)
Azure Key Vault
Azure DevOps or GitHub
CI/CD Pipelines
Proven core skills
Azure Databricks
Apache Spark
Spark SQL
SQL Development
Python Programming
Apache Airflow
DAG Development and Workflow Orchestration
Delta Lake
Azure Data Lake Storage (ADLS)
ETL / ELT Development
Data Warehousing Concepts
Data Modeling Fundamentals
Preferred Qualifications
- Azure Databricks certification or related Azure certifications
- Experience working with Healthcare, Claims, Member, Provider, Payment Integrity, or Affordability data domains
- Experience with Snowflake and modern cloud data platforms
- Experience using GitHub Actions, DevOps automation, and Infrastructure as Code
- Healthcare payer industry experience
- Experience supporting enterprise data platforms and analytics ecosystems
- Experience with Payment Integrity, Risk Adjustment, Claims Analytics, or Provider Analytics
- Exposure to AI/ML data engineering workflows and AI-enabled analytics solutions
- Exposure to Generative AI, Azure OpenAI, or AI-assisted engineering tools
- Understanding of Data Lakehouse, Data Mesh, or Data Fabric concepts
- Exposure to AI-driven development and engineering productivity tools
Key Competencies
Solid analytical and problem-solving skills
Ability to independently deliver medium to complex technical solutions
Solid debugging and troubleshooting capabilities
Excellent written and verbal communication skills
Effective stakeholder collaboration and teamwork
Solid learning agility and growth mindset
Ability to work in a fast-paced and dynamic environment
Self-motivated with solid ownership and accountability
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.
Job description provided by UnitedHealth Group.
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