Senior Quality Engineer

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 diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. Primary Responsibilities Design, build, and maintain scalable data quality frameworks to validate accuracy, completeness, consistency, and timeliness of enterprise data across multiple data domains Develop and automate data quality checks and controls using SQL, Python, and PySpark notebooks within a Databricks environment Implement data validation, reconciliation, and anomaly detection logic across batch and streaming data pipelines Embed automated data quality checks into ETL / ELT pipelines to enforce quality gates and prevent defective data from propagating downstream Build reusable data quality automation components, libraries, and frameworks that can be consistently adopted across data engineering teams Validate Power BI datasets, semantic models, and dashboards by ensuring: Sourcetoreport data reconciliation Metric and KPI accuracy Aggregation, filter, and refresh correctness Partner with reporting and analytics teams to validate Power BI measures, calculations, and business logic against certified data sources Monitor and report on data quality metrics and trends, including dashboardlevel data accuracy and consistency Perform root cause analysis for data quality and reporting issues, collaborating with upstream data producers and downstream consumers to drive permanent fixes Leverage AIassisted data quality practices, including: GenAIbased rule generation and test case creation Intelligent anomaly detection and pattern recognition Automated triage and summarization of data quality issues Enable AIOpsstyle data observability, using AIdriven insights to proactively identify data drift, schema changes, and metric anomalies Support governance and audit readiness by ensuring data quality controls, validations, and dashboard certifications are documented and traceable Continuously improve data quality practices through automation, standardization, and AIdriven enhancements, reducing manual validation effort Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI You’ll be rewarded and recognized for your performance in an environment that will challenge you and give your clear directions on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications Bachelor's degree in Computer Science, Engineering, or IT related field 5+ years of experience in data quality engineering, quality engineering, or data engineering roles with a strong focus on automation and frameworks with a solid understanding of data quality dimensions (accuracy, completeness, consistency, timeliness, validity) 5+ years of experience with SQL for data profiling, reconciliation, and validation 5+ years of experience implementing automated data quality frameworks embedded within ETL / ELT workflows 3+ years of experience in Python and PySpark, including building reusable notebooks and automation frameworks 3+ years of proven experience working in a Databricks environment, supporting largescale data pipelines and analytics platforms 2+ years of handson experience validating Power BI datasets, dashboards, KPIs, and metrics against source systems Preferred Qualifications Strong communication skills with the ability to translate business reporting requirements into technical quality controls *All Telecommuters 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 to $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 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. #J-18808-Ljbffr