Senior Data Engineer

UnitedHealth Group•Eden Prairie, MN

21h•$91,700 - $163,700•Remote

About The Position

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, and data 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.

Requirements

Bachelor's degree
5+ years of experience in database architecture, data engineering, data modeling, data warehousing, ETL/ELT development, or cloud data platform engineering
5+ years of experience writing SQL and developing data integration or data provisioning solutions
5+ years of experience with data security, governance, quality, privacy, access management, and compliance practices
2+ years of experience with one or more cloud platforms and their data services

Nice To Haves

Experience coaching, mentoring, or guiding other employees
Ability to assess customer needs and translate business and technical concepts into practical solutions
Ability to solve moderately complex problems and conduct moderately complex analyses with minimal guidance
Ability to work independently on complex, less-structured assignments
Strong communication skills, including the ability to explain difficult technical issues to technical and non-technical audiences

Responsibilities

Design, implement, and maintain enterprise database, data warehouse, data lake, lakehouse, and cloud data architectures
Develop scalable solutions using Platform-as-a-Service and cloud technologies, with a focus on data stores and associated ecosystems
Design data models, schemas, data structures, and integration patterns to support operational, analytical, and AI workloads
Develop and optimize SQL, data markup scripts, ETL/ELT pipelines, data ingestion processes, and data provisioning solutions
Establish and enforce data quality, data governance, metadata management, security, privacy, and compliance standards
Provide database and cloud platform sizing, configuration, capacity planning, performance tuning, and optimization guidance
Conduct needs assessments and analyze current business practices, processes, and procedures to identify opportunities for improving data accessibility and usage
Evaluate future business opportunities for leveraging data storage, retrieval, analytics, machine learning, and artificial intelligence capabilities
Design and support data platforms that enable reporting, advanced analytics, predictive modeling, machine learning, and generative AI applications
Develop AI-ready data foundations, including feature data, vector storage, embeddings, retrieval-augmented generation, model-serving data, and real-time or batch data pipelines
Partner with data scientists, AI engineers, application developers, and business teams to operationalize machine learning and AI solutions
Help establish responsible AI practices, including data lineage, model monitoring, explain ability, access controls, risk management, and appropriate use of sensitive data
Support the development of analytics and applications that build on enterprise data platforms
Assess non-standard technical requests and recommend practical, scalable, and cost-effective solutions
Analyze the architectural impact of software, hardware, cloud, and data acquisition vendor strategies
Manage relationships with software and hardware vendors and participate in product evaluations, technical reviews, and roadmap discussions
Provide technical guidance, explanations, and recommendations to stakeholders on complex data and AI architecture issues
Select, develop, and evaluate personnel to ensure the efficient operation of the function
Coach team members, provide feedback, share knowledge, and serve as a resource for less-experienced employees
Establish standards, patterns, documentation, and reusable practices for data engineering, cloud architecture, and AI platform development
Participate in architecture reviews, solution design, risk assessments, implementation planning, and production support activities