Associate Data Engineering Manager

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 inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Design, build, and maintain scalable data pipelines and data platforms using modern programming languages, cloud data warehouses, and distributed data processing frameworks Develop resilient data architectures across data warehouses, data lakes, Lakehouse platforms, and streaming environments to support enterprise reporting, business intelligence, advanced analytics, and machine learning use cases Lead end-to-end delivery of analytics data products, from requirements understanding and solution design through development, deployment, production support, monitoring, and performance optimization Serve as a Scrum Master / Agile delivery lead for data engineering workstreams by facilitating sprint planning, daily stand-ups, backlog refinement, sprint reviews, retrospectives, and release planning Perform PMO and delivery governance activities including project tracking, dependency management, RAID management, sprint progress reporting, stakeholder updates, and timely escalation of risks, issues, and blockers Collaborate with business stakeholders, product owners, data engineering teams, analytics teams, and data science partners to translate business needs into scalable, secure, and reusable data solutions Ensure data security, governance, quality, lineage, standardization, and compliance are embedded across data pipelines, platforms, and analytics data products Build, optimize, and support ETL/ELT pipelines, data models, orchestration workflows, and reusable data assets that improve reliability, performance, and maintainability Drive continuous improvement in engineering practices through code reviews, technical documentation, automation, CI/CD adoption, monitoring standards, and platform optimization Mentor and guide junior data engineers by sharing best practices, supporting technical problem-solving, and promoting a culture of ownership, collaboration, and delivery excellence Create and deliver clear technical updates, delivery status summaries, and stakeholder communications for both technical and non-technical audiences, ensuring transparency and alignment across teams Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Builder Responsibilities: Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making Required Qualifications: Bachelor's or master's degree in computer science, Engineering, Information Systems, Data Science, or a related technical field 7+ years of relevant experience in Data Engineering, Analytics Engineering, Data Platform Development, or enterprise data solution delivery Solid hands-on expertise in Python and/or Scala/Java for building scalable data pipelines, automation frameworks, and production-grade data solutions