Senior Manager, Data Engineering - Remote
About The Position
Optum Insight at Optum Technology is seeking a Senior Manager of Data Engineering to lead data engineering initiatives and a team responsible for designing, building, and maintaining enterprise data architectures and scalable integration pipelines. The role focuses on providing reliable, secure, high-performance data platforms that support health technology solutions and actionable insights across the organization. The position may be performed remotely from anywhere in the U.S. Hires in the Minneapolis or Washington, D.C. area must work in the office at least four days per week. Remote employees must follow UnitedHealth Group’s Telecommuter Policy. The role offers a comprehensive benefits package, incentive and recognition programs, equity stock purchase, and 401(k) contribution, subject to eligibility requirements. Annual salary is $112,700–$193,200 based on full-time employment and factors including labor market, education, work experience, and certifications. The position is subject to a pre-employment drug test.
Requirements
- Bachelor’s degree or at least 4 years of equivalent data engineering experience in lieu of a degree.
- At least 8 years of professional experience in data engineering, data warehousing, or enterprise data architecture.
- At least 5 years of experience designing and implementing complex ETL/ELT pipelines and data integration workflows.
- At least 4 years of hands-on experience with SQL and relational or non-relational database technologies, such as PostgreSQL, MySQL, Snowflake, or MongoDB.
- At least 3 years of direct people management or technical leadership experience leading data engineering or software development teams.
- At least 3 years of experience with enterprise cloud data platforms such as AWS, Azure, GCP, or Databricks.
Nice To Haves
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, or a related technical field.
- Experience with big data technologies and distributed computing frameworks such as Apache Spark, Hadoop, or Kafka.
- Experience with data modeling methodologies such as Star Schema, Data Vault, or Dimensional Modeling.
- Experience implementing CI/CD pipelines, DevOps practices, and Infrastructure as Code for data workflows.
- Familiarity with data governance tools, data cataloging, and data lineage platforms.
Responsibilities
- Lead and manage data engineering teams in designing, developing, and maintaining scalable data architecture, pipelines, and data integration solutions.
- Oversee end-to-end data lifecycle operations, ensuring data quality, governance, security, and compliance across enterprise data platforms.
- Collaborate with product, analytics, and business stakeholders to define data strategies and deliver actionable insights aligned with organizational goals.
- Establish data engineering best practices, architectural frameworks, and design standards to optimize platform performance and reliability.
- Continuously optimize cloud and on-premise data pipelines, ETL/ELT workflows, and database infrastructure.
- Mentor and develop engineering staff, fostering a collaborative, high-performance, continuous-learning culture.
Benefits
- Comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401(k) contribution
- Development opportunities for other roles
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What This Job Offers
Job Type
Full-time
Career Level
Senior
