Sr Dir Software - Data Platform Engineer - Minneapolis

UnitedHealth Group•Minneapolis, MN

16h•$159,300 - $273,200

About The Position

Optum Tech’s Software / Data Engineering team builds scalable software systems, data architecture, and AI platform foundations that support enterprise needs and next-generation intelligent products. Supporting UnitedHealthcare Technology's Chief Technology Organization, the team delivers enterprise platforms, engineering standards, and architectural capabilities for business, financial, operational, and AI-driven initiatives. The role leads a large engineering organization and drives the design and implementation of reference architectures, engineering standards, and platform capabilities across the organization. It combines hands-on technical leadership with organizational leadership: the position holder will grow and run a large team, implement reference architectures in production directly and through teams, and personally lead pilots to validate architectural decisions before scaling them. The work includes establishing an AI-ready data layer, developing cloud-native infrastructure and data platforms, and ensuring consistency, scalability, and observability across teams. The role partners with product, data, infrastructure, security, and other leaders to align platform delivery with long-term business goals.

Requirements

15+ years of experience in software engineering, data engineering, distributed systems, platform engineering, or related technical disciplines, with 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 or lakehouses, streaming systems, cloud-native applications, and enterprise platforms.
10+ years of hands-on programming experience in Python, Java, Go, SQL, or similar languages, including the ability to prototype solutions, review complex codebases, and contribute to production-quality implementations.
10+ years of experience driving technology adoption and architectural modernization with Product, Data, AI/ML, Security, Infrastructure, and Enterprise Architecture leaders in large-scale organizations.
7+ years of experience designing and operating modern data platforms using distributed processing technologies such as Spark or Flink; streaming platforms such as Kafka, Kinesis, or Pub/Sub; orchestration frameworks such as Airflow; and cloud-native data platforms such as Snowflake, Databricks, or BigQuery.
7+ years of experience in senior technology leadership roles, 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 such as AWS, Azure, or GCP, including infrastructure architecture, reliability engineering, security, observability, performance optimization, and cost management.
3+ years of experience designing, implementing, or scaling AI-powered systems, including RAG, agentic workflows, LLM-enabled applications, vector databases, embeddings infrastructure, feature platforms, or 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 and driving adoption of operating models, technologies, and business processes in 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 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 reference architectures and platform capabilities for the software, data, and AI foundation, including feature stores, vector stores, embeddings infrastructure, and retrieval pipelines.
Translate technology trends, AI frameworks, and architectural patterns into reference architectures and operationalize them across the engineering organization.
Validate major architectural decisions through hands-on pilots or proofs of concept before scaling them into production.
Lead, grow, and mentor a large organization of software, data, and platform engineers and technical leaders; hire and develop managers and raise architectural standards.
Build and implement high-throughput, cloud-native application infrastructure, data pipelines, and intelligent services for large-scale enterprise workloads.
Partner with product, data, infrastructure, and security leadership to align engineering execution and platform delivery with business goals.
Establish and enforce engineering standards for observability, scalability, consistency, reference patterns, and design reviews across teams.