> Markdown version of [/jobs/ext/240682-senior-data-engineer](https://www.wearedevelopers.com/jobs/ext/240682-senior-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Optum, Inc - **Location:** Eden Prairie, MN, United States (Remote available) - **Experience:** Expert - **Salary:** $91,700.0 - $163,700.0 - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Business Analytics Applications, Audit Trail, Microsoft Azure, Cloud Computing, Computer Programming, Continuous Integration, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, Data Warehousing, DevOps, Dimensional Modeling, Python (Programming Language), Meta-Data Management, Software Architecture, Software Technical Review, Workflow Management Systems, Azure Service Bus, Cloud Platform System, Data Ingestion, Sql Optimization, System Availability, Snowflake, Apache Spark, Data Strategy, Cloudformation, Data Layers, Containerization, Data Lakes, Kubernetes, Data Lineage, Real Time Data, Apache Kafka, Data Management, Terraform, Data Pipelines, Docker, Databricks - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=8ae0639bcc380726 ## About the Role * 7+ years of experience in the following: + Modern data engineering stacks + Apache Spark, Databricks, Snowflake + Data ingestion frameworks and large-scale ETL/ELT pipelines + Cloud platforms + Hands-on experience with AWS, Azure, or GCP + Data modeling and storage + Dimensional modeling, normalized and denormalized schemas + Data lakes, lake house architecture, and data warehouses + Data quality and governance + Data quality frameworks, anomaly detection, data validation + Data lineage, metadata management, and cataloging tools + Kafka, Kinesis, Event Hubs, or similar technologies + Workflow orchestration + Airflow, Databricks Workflows, Prefect, or similar tools + Programming + Python and/or Scala + Advanced SQL for analytics and transformations + DevOps and platform engineering + CI/CD for data pipelines + Infrastructure as Code (Terraform, CloudFormation, ARM) + Containerization (Docker, Kubernetes - preferred) + Leading high-performing data engineering teams * 3+ years of experience in a technical leadership or people management role Preferred Qualifications: * Master's degree * Experience in streaming and real-time data Soft Skills: * Ability to translate business needs into scalable technical solutions * Experience driving architectural decisions and influencing senior leadership * Excellent written and verbal communication skills * Strong stakeholder management and cross-functional collaboration skills * All Telecommuters will be required to adhere to UnitedHealth Group's Telecommuter Policy. ## Description * Lead and scale data engineering teams * Manage, mentor, and grow a team of data engineers across multiple experience levels * Set technical direction, establish best practices, and conduct design and code reviews * Partner with product, analytics, data science, and platform teams to deliver business outcomes * Architect and deliver enterprise-scale data platforms * Design, build, and evolve scalable data architectures using Spark, Databricks, and Snowflake * Own end-to-end data pipelines for batch and streaming ingestion * Ensure high availability, performance, and cost efficiency of data platforms * Data pipeline and platform ownership * Develop and oversee robust data ingestion, transformation, and orchestration pipelines * Implement and enforce data quality, validation, normalization, and reconciliation frameworks * Establish and maintain data lineage, metadata management, and observability * Enable analytics, ML, and feature development * Build and manage feature stores and curated data layers for analytics and ML use cases * Partner with data science teams to productionize ML data pipelines * Support self-service analytics and data democratization initiatives * Governance, security, and compliance * Implement data governance standards including access control, encryption, and auditability * Ensure compliance with enterprise and regulatory requirements (e.g., HIPAA) * Define SLAs, SLOs, and operational monitoring for data systems * Strategic planning and execution * Drive roadmap planning, capacity planning, and prioritization for data engineering initiatives * Evaluate and onboard new tools and technologies * Influence data strategy and platform modernization efforts at the enterprise level You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear directions on what it takes to succeed in your role as well as provide development for other roles you may be interested in. ## Related Videos - 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