Requisition Number: 2374167 Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us to start Caring. Connecting. Growing together. We are seeking a Senior Azure Data Engineer to help design, build, and operate our next-generation enterprise data platform on Microsoft Azure. You will own end-to-end delivery of data pipelines and data products that power analytics, regulatory reporting, operational dashboards, and emerging AI/ML use cases. You will partner closely with data architects, analytics engineers, data scientists, business stakeholders, and platform engineering teams to deliver reliable, performance, secure, and cost-efficient data solutions. This role is ideal for an engineer with solid hands-on depth in Azure Data Factory, Azure Synapse Analytics and/or Databricks, and modern Lakehouse patterns, who is comfortable leading migration programs (e.g., Informatica-to-ADF, on-prem warehouse-to-cloud), mentoring mid-level engineers, and shaping engineering standards across the team. You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. Primary Responsibilities: - Pipeline Design & Development - Design and build robust, reusable, parameter-driven ingestion and transformation pipelines using Azure Data Factory, Synapse Pipelines, Data Bricks and/or Microsoft Fabric Data Factory - Implement medallion architecture (Bronze / Silver / Gold) on Azure Data Lake Storage Gen2 using Delta Lake, Parquet, and structured streaming patterns - Build performant ELT workflows that leverage pushdown to source systems (Synapse Dedicated SQL Pool, Azure SQL, Teradata) where appropriate - Develop and optimize PySpark notebooks and jobs on Azure Databricks or Synapse Spark - Data Modeling & Warehousing - Design dimensional models (Kimball star/snowflake) and data vault patterns for analytics consumption - Implement Slowly Changing Dimensions (Type 1/2/3), Change Data Capture, and late-arriving data patterns - Tune distributed SQL workloads in Synapse Dedicated SQL Pool / Fabric Warehouse, including distribution keys, partitioning, and clustered column store indexes - Platform Engineering & DevOps - Implement CI/CD for data pipelines using Azure DevOps (YAML pipelines, ARM/Bicep/Terraform) across Dev / SIT / UAT / Prod environments - Instrument pipelines with robust logging, auditing, and monitoring using Azure Monitor, Log Analytics, and KQL - Define and enforce coding standards, code review practices, branching strategies, and release management - Migration & Modernization - Lead or contribute to legacy-to-cloud migrations - e.g., Informatica PowerCenter to Azure Data Factory, on-premises Teradata / Oracle / SQL Server to Synapse or Fabric - Perform workload assessment, capacity planning, and cost modeling for target-state architectures - production incident response for critical pipelines You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications: - Demonstrated experience in Data Bricks and PySpark - Production experience with one or more of: Azure Synapse Analytics (Dedicated and Serverless SQL Pools, Spark Pools) OR Azure Databricks (Delta Lake, Unity Catalog) OR Microsoft Fabric (Warehouse, Lakehouse, OneLake) - Experience with Azure Key Vault, Azure AD / Entra ID (including managed identities and service principals), and private networking (VNet integration, private endpoints) - Experience with monitoring and troubleshooting with Azure Monitor, Log Analytics, and KQL - Deep hands-on expertise with Azure Data Factory: pipelines, datasets, linked services, triggers, parameterization, mapping data flows, and all three Integration Runtime types (Azure, Self-hosted, SSIS) - Demonstrated working knowledge of Azure Data Lake Storage Gen2 (hierarchical namespace, RBAC + ACLs, lifecycle management, security) - Proficient in T-SQL; familiarity with Spark SQL, KQL, PowerShell, and Bash shell scripting - Advanced SQL - window functions, CTEs, query optimization, execution plan analysis, performance tuning - Demonstrated Python for data engineering - pandas, PySpark, REST API integration, unit testing (pytest) - Willing/able to travel approximately 10% of the time as business needs dictate (occasional travel to Springfield, IL two to three times per year) Preferred Qualifications: - 5+ years of data warehouse development experience - 5+ years of data modeling experience using ERWIN or similar tools - 2+ years of experience with Azure Data Factory and Snowflake - Medicaid Domain Knowledge *All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 - $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants. 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. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.

• Develop pipelines in Spark (Python) in the Databricks Platform • Build cross-functional working relationships with business partners in Food Analytics, Operations, Marketing, and Web/App Development teams to power pipeline development for the business • Ensure system reliability and performance • Deploy and maintain data pipelines in production • Set an example of code quality, data quality, and best practices • Work with Analysts and Data Engineers to enable high quality self-service analytics for all of Hungryroot • Investigate datasets to answer business questions, ensuring data quality and business assumptions are understood before deploying a pipeline

• Own the data architecture across OneOcean's data organisation — operational, lakehouse, analytical-serving and vector layers — providing a coherent target state and a pragmatic path to it. • Lead the discovery, documentation and specification of the data structures and models required to support product and analytics roadmaps. • Reverse-engineer source data from OneOcean SaaS products — building accurate logical models of upstream systems and identifying the data contracts, grain and semantics our pipelines depend on. • Design the right data store for each use case — choosing between OLTP, columnar / OLAP, lakehouse and vector approaches; making the trade-offs explicit. • Define and maintain conceptual, logical and physical data models; produce clear ERDs, lineage and dimensional designs (star / snowflake, conformed dimensions, surrogate keys). • Establish and enforce modelling standards, naming conventions, data contracts and schema-evolution practices across teams. • Partner with the Data Team Lead, BI Team Lead and AI Team Lead — translating product and analytics needs into specifications their engineers can build from, and unblocking architectural decisions as they arise. • Collaborate with Product, Architecture and Engineering Team Leads to align data direction with the wider engineering strategy. • Champion data governance — cataloguing, lineage, ownership, quality, security and privacy. • Document architectural decisions (ADRs) so the why is preserved alongside the what. • Mentor engineers across the data organisation on modelling, design and architectural reasoning — without line-managing them. • Stay current with the data landscape and bring in proven techniques as they mature; foster a culture of continuous improvement, innovation and knowledge sharing.

• Design and implement scalable data models, storages and pipelines for critical product features • Drive the evolution of our data platform to meet future needs of real-time big data processing • Create and evolve architectural roadmaps for the data platform • Turn product requirements into viable and scalable data architectures and implementations • Act as a bridge between data science, product engineering, and stakeholders • Establish and follow data governance frameworks, standards, and best practices • Mentor senior engineers and architects on complex data modeling and distributed system challenges