Senior Data Engineer
About The Position
Optum is hiring a Senior Data Engineer to support its Identity Management rebuild initiative and the ongoing support of the existing application. The role involves building and supporting AI-enabled data pipelines to improve automation, monitoring, testing, data quality validation, and workflow efficiency. The engineer will work across development, staging, and production environments, supporting ingestion, transformation, serving, monitoring, and data quality for distributed processing workloads while following governance, privacy, and security expectations. The role also supports the build and operationalization of custom AI agents and the use of enterprise-approved generative AI tools to assist with engineering, testing, documentation, troubleshooting, production support, and workflow automation. The position is telecommutable from anywhere within the United States, subject to UnitedHealth Group’s Telecommuter Policy.
Requirements
- Bachelor’s degree.
- At least 5 years of hands-on data engineering experience building, supporting, and operating data pipelines and data platforms.
- At least 4 years of proficiency in Python for programming, automation, data processing, and scripting.
- At least 4 years of Azure Databricks experience, including pipeline development, job monitoring, workload support, performance tuning, and cost-aware development practices.
- At least 4 years of PySpark experience for distributed data processing, transformations, data quality validation, and performance tuning.
- At least 3 years of Git experience, including CI/CD basics, version control, pull request workflows, branching strategies, and release support.
- At least 1 year of basic working understanding of data governance, data security, access controls, privacy, and enterprise compliance concepts.
- Adherence to UnitedHealth Group’s Telecommuter Policy.
- Pass a drug test before beginning employment.
Responsibilities
- Build, enhance, and support Azure data pipelines and data solutions for the Identity Management rebuild and existing application.
- Develop and support data pipelines using Azure Databricks, Azure Data Factory, PySpark, Python, and Git-based development practices across development, staging, and production environments.
- Troubleshoot data issues, improve pipeline reliability, and contribute to performance tuning and cost optimization.
- Support ingestion, transformation, serving, monitoring, and data quality activities for distributed processing workloads while following data governance, privacy, and security expectations.
- Support the build and operationalization of custom AI agents for development, testing, documentation, data validation, monitoring, production support, runbook execution, and data workflow automation.
- Use Databricks Genie, GitHub Copilot, Microsoft 365 Copilot, and other enterprise-approved GenAI tools to accelerate pipeline development, automation, troubleshooting, documentation, analysis, and decision-making workflows.
- Maintain a minimum of 90% weekly usage of approved AI tools and leverage AI tools and agents to enhance coding, documentation, data analysis, testing, and delivery workflows.
- Collaborate with stakeholders, platform engineering, analytics, and application teams to support delivery priorities and clearly communicate risks, dependencies, and progress.
- Stay current with evolving AI capabilities and apply them to improve delivery quality, efficiency, innovation, and responsible engineering practices.
Benefits
- Comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401(k) contribution
- Career development opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Senior
