Sr Dir Software - Data Platform Engineer - Minneapolis

UnitedHealth Group•Minneapolis, MN

5d•$159,300 - $273,200•Onsite

About The Position

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. Based in Eden Prairie, MN, our Software / Data Engineering team builds the scalable software systems, data architecture, and AI platform foundation that power the enterprise and enable next-generation intelligent products—rethinking how enterprise data and applications are architected, served, and governed across cloud platforms. Supporting UnitedHealthcare Technology's Chief Technology Organization, this team delivers the enterprise platforms, engineering standards, and architectural capabilities that underpin critical business, financial, operational, and AI-driven initiatives across UHC Technology. In this role, you will lead a large engineering organization and be the driving force behind implementing the reference architectures, engineering standards, and platform capabilities the organization runs on, establishing consistency, scalability, and observability across every team. This is a hands-on engineering leadership role: you'll grow and run a large team, roll out reference architectures into production yourself and through your teams, and stay grounded in reality by personally running hands-on pilots to prove out what you're putting into practice before scaling it across the organization.

Requirements

15+ years of experience in software engineering, data engineering, distributed systems, platform engineering, or related technical disciplines, with a proven track record of increasing responsibility building production platforms and leading engineering teams
10+ years of hands-on experience building, scaling, and operating production software and data platforms, including data pipelines, warehouses/lakehouses, streaming systems, cloud-native applications, and enterprise-scale platforms serving mission-critical product and analytics workloads
10+ years of hands-on programming experience in Python, Java, Go, SQL, or similar languages, with the ability to personally prototype solutions, review complex codebases, and contribute to production-quality implementations
10+ years of experience driving technology adoption and architectural modernization through partnership with Product, Data, AI/ML, Security, Infrastructure, and Enterprise Architecture leaders across large-scale organizations
7+ years of experience designing and operating modern data platforms utilizing distributed processing technologies (Spark, Flink, or equivalent), streaming platforms (Kafka, Kinesis, Pub/Sub), orchestration frameworks (Airflow or similar), and cloud-native data platforms such as Snowflake, Databricks, BigQuery, or equivalent
7+ years of experience in senior technology leadership roles, including Senior Director, Director, Principal Engineer, Distinguished Engineer, or equivalent positions, leading large, multi-team engineering organizations and driving enterprise engineering standards and architectural direction
5+ years of experience building and operating solutions in cloud-native environments (AWS, Azure, GCP, or equivalent), including knowledge of infrastructure architecture, reliability engineering, security, observability, performance optimization, and cost management
3+ years of experience designing, implementing, or scaling AI-powered systems, including retrieval-augmented generation (RAG), agentic workflows, LLM-enabled applications, vector databases, embeddings infrastructure, feature platforms, and model-serving architectures
Demonstrated success leading engineering organizations of 60+ employees across multiple teams and geographies, including hiring, organizational design, talent development, succession planning, and manager coaching
Experience leading enterprise-wide organizational change initiatives, including driving adoption of new operating models, technologies, and business processes across large, complex, matrixed organizations
Proven experience establishing and implementing enterprise engineering standards, reference architectures, platform capabilities, governance models, and reliability practices across multiple engineering teams
Demonstrated ability to influence executive stakeholders and drive large-scale organizational change through technical expertise, engineering credibility, data-driven decision-making, and delivery of measurable business outcomes

Nice To Haves

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field. Advanced degree
Experience implementing reference architectures and platform standards at scale in a high-growth product or platform organization where software and data are core products
Background in ML engineering, MLOps, or applied AI infrastructure in addition to core software engineering leadership
Demonstrated track record of replacing or modernizing large legacy systems with modern cloud architectures
Active involvement in the technical community through open-source contributions, technical publications, or industry conference presentations

Responsibilities

Design and implement the reference architectures and platform capabilities for the company's software, data, and AI foundation—including the AI-ready data layer (feature stores, vector stores, embeddings infrastructure, retrieval pipelines) that turns raw data into something a model can reason over—and drive their adoption into production across teams
Translate modern technology trends, AI frameworks, and architectural patterns into concrete reference architectures, then implement and operationalize them across the broader engineering organization
Prove out major architectural decisions with a hands-on pilot or proof-of-concept before rolling them into production at scale—staying close enough to the code and the data to know whether an architecture actually holds up under real workloads
Lead, grow, and mentor a large organization of senior software and data engineers, platform engineers, and technical leaders—hiring, leveling, and developing managers, and raising the architectural bar across every team
Build and implement high-throughput, cloud-native application infrastructure, data pipelines, and intelligent services that handle large-scale enterprise workloads reliably and efficiently
Partner cross-functionally with product, data, infrastructure, and security leadership to align engineering execution and platform delivery with long-term business goals
Establish and enforce engineering standards for observability, scalability, and consistency across a large, multi-team organization, along with reference patterns and design review practices that raise the bar for everyone building against them