Principal Data Engineering

UnitedHealth Group•Eden Prairie, MN

12h•$112,700 - $193,200•Remote

About The Position

The Principal Data Engineer is a senior technical leader within the OHBI program, responsible for designing, building, and evolving enterprise-scale, AI-enabled data platforms that power analytics, reporting, and machine learning. This role combines hands-on engineering with architectural leadership, owning end-to-end data platform design across Azure, Snowflake, dbt, and modern Lakehouse technologies. The Principal Data Engineer sets engineering standards, ensures production excellence, and serves as a key partner to architecture, product, analytics, and data science teams. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

Extensive experience with cloud data platforms, especially Azure and Snowflake
Solid hands-on expertise in: SQL and Python
Azure Data Factory - Data pipeline design and orchestration
Snowflake - tasks and steams design and orchestration
Deep understanding of data integration patterns (batch, micro-batch, streaming, near real-time)
Experience with data quality, observability, monitoring, and production support
Proven ability to design for performance tuning, scalability, and cost optimization
Experience enabling AI/ML data pipelines and solutions
Experience in implementing a new platform including new technologies and solutioning to ensure the business needs are met before technology needs
Demonstrated technical leadership and mentorship experience

Nice To Haves

Bachelor’s degree, Computer Science or related field
Experience with Databricks and/or modern data ecosystem tools
Familiarity with BI/Analytics platforms (e.g., Power BI)
Prior experience within Optum / UHG environments
Experience with Lakehouse patterns and Apache Iceberg
Solid communication skills with ability to influence senior stakeholders

Responsibilities

Partner closely with Platform Solution Architect to evolve the end-to-end data platform architecture across Azure, Snowflake, dbt, and future architecture changes using lake house technologies (including Iceberg where applicable)
Define reference architectures, reusable frameworks, and engineering standards for ingestion, transformation, and consumption
Partner with Platform Solution Architect Drive decisions around scalability, performance, resiliency, security, and cost optimization
Partner with Tech Engineering Delivery Owner / Platform Architect / Data Architect / Offshore Tech Lead and Offshore Snowflake Admin defining best practices, data models, integration patterns, and implementation strategies
Design, build, and operate high-volume, high-reliability batch and near real-time data pipelines using Azure Data Factory, dbt, Python, SQL, Snowflake, and related tools
Implement scalable transformation logic to deliver trusted, analytics-ready datasets
Support event-driven and streaming architectures were needed
Apply canonical/common data modeling practices to ensure consistency and reusability across domains
Enable AI/ML and GenAI use cases by building AI-ready data platforms and pipelines
Support: Feature engineering and model training pipelines, Historical and point-in-time datasets, Data versioning and ML lifecycle integration
Leverage enterprise tools such as Snowflake Cortex and MCP Server deliver governed AI capabilities
Partner closely with Data Science and ML Engineering teams to enable scalable, production-ready AI solutions
Establish and enforce data quality, observability, reconciliation, and auditability standards
Own production stability, including monitoring, incident response, root cause analysis, and long-term remediation
Implement practices for schema evolution, backward compatibility, and error handling
Define and track KPIs for data freshness, pipeline reliability, platform performance, and cost efficiency
Design and manage CI/CD pipelines for data and ML workloads, including automated testing and release orchestration
Ensure alignment with enterprise governance, security, and regulatory requirements (HIPAA, SDLC, data governance)
Implement lineage, monitoring, and audit frameworks to support compliance and traceability
Serve as a senior technical authority and escalation point, driving solution design and resolving complex challenges
Provide design reviews, code reviews, and technical guidance to engineers across levels
Mentor and develop engineers, fostering a culture of engineering excellence, ownership, and accountability
Influence cross-team delivery and coordinate across onshore/offshore teams and stakeholders
Operate independently with platform-level ownership and accountability
Balance hands-on execution with long-term architecture thinking and working with senior architect for OHBI
Influence engineering strategy beyond immediate team scope
Act as a trusted partner across engineering, architecture, and business teams
Translate business and product requirements into scalable technical solutions and delivery plans
Partner with data architecture, analytics, BI, and product teams to ensure alignment and value delivery
Communicate complex technical concepts effectively to both technical and non-technical stakeholders