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.
Primary Responsibilities:Modernization Strategy & Migration Roadmap
- Own and execute the engineering strategy for modernizing applications, translating business outcomes (cost reduction, resilience, scalability, time-to-market) into a prioritized migration roadmap and quarterly delivery plan
- Define the target-state architecture on Azure cloud, including landing zones, networking, identity, data platform (Databricks, MongoDB), and application runtime patterns (containers, serverless, managed services)
- Lead portfolio-level assessment of legacy applications: rationalization, disposition decisions (retire, retain, rehost, replatform, refactor, rebuild, replace), migration waves, and dependency sequencing
Technical Leadership & Architecture (Migration + Engineering Excellence)
- Provide hands-on technical leadership across solution design, architecture, and implementation for migration and modernization efforts; ensure solutions are reliable, secure, performant, and maintainable
- Establish reference architectures and engineering standards for cloud-native applications on Azure, including microservices patterns, event-driven designs, API gateways, data flows, service boundaries, observability, and performance engineering
- Drive technology decisions across the core stack: Azure (AKS, App Service, Functions, Event Hubs, API Management), Databricks (lakehouse, Delta Lake, Unity Catalog, pipelines), MongoDB (schema design, sharding, Atlas), Python (services, data engineering), and Java (Spring Boot, enterprise services)
- Lead build/buy/partner evaluations for migration tooling, schema conversion, data replication (e.g., Azure Database Migration Service, Qlik, Fivetran), and refactoring accelerators
- Drive reusable components and accelerators (migration factory patterns, shared libraries, common services, IaC modules) to improve delivery efficiency and consistency across waves
Delivery Ownership (End-to-End Modernization Lifecycle)
- Accountable for the end-to-end engineering lifecycle, discovery, assessment, architecture and design, build, data migration, testing (including parallel run and reconciliation), cutover, hypercare, and decommissioning of legacy systems
- Own delivery commitments: scope, schedule, budget, quality, and risk; proactively surface and resolve blockers, manage dependencies across teams, and drive on-time wave completion
- Institutionalize engineering rigor: code quality, testing strategy (unit, integration, contract, performance, data parity), CI/CD discipline, IaC (Terraform/Bicep), reliability targets, and incident response readiness
- Establish migration playbooks covering data migration patterns, dual-write and backfill strategies, cutover runbooks, rollback plans, and production validation
Data Platform Modernization
- Lead data modernization initiatives: migrating from legacy databases (SQL Server, Oracle, DB2, mainframe) to Databricks lakehouse and MongoDB operational stores, with clear separation of analytical and transactional workloads
- Define data architecture standards: ingestion patterns, medallion architecture (bronze/silver/gold) on Databricks, governance via Unity Catalog, data quality, lineage, and access control
- Ensure data integrity through migration: reconciliation frameworks, parallel-run validation, defect triage, and sign-off gates before cutover
AI-Enabled Modernization (≈20% of scope)
- Embed AI and intelligent automation into modernized workflows where it drives measurable value, decision support, document intelligence, and workflow automation integrated with the modern Azure/Databricks/MongoDB stack
- Leverage AI-assisted engineering tools (code analysis, legacy code understanding, test generation, refactoring copilots) to accelerate migration velocity and reduce risk
- Partner with AI/ML teams to ensure modernized platforms are AI-ready: feature stores on Databricks, vector search where relevant, clean APIs, and observability hooks that support future AI use cases
- Apply responsible AI practices, risk assessment, controls, auditability, and governance, to any AI capability embedded in workflows
You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications:- Undergraduate degree or equivalent experience
- 12+ years of progressive software engineering experience
- 6+ years owning end-to-end delivery of large-scale application modernization and cloud migration programs in enterprise or regulated environments
- 6+ years of hands-on experience with Azure cloud (AKS, App Service, Functions, Event Hubs, API Management, Azure SQL, networking, identity, IaC with Terraform or Bicep)
- 6+ years of production software development experience in Python and Java (including Spring Boot, microservices, REST APIs)
- 6+ years of experience in modern software engineering practices: cloud-native architectures, CI/CD, automation, testing, and production operations
- 6+ years of experience establishing engineering standards and reference architectures across multiple teams
- 5+ years of hands-on experience designing and delivering solutions on Databricks (Delta Lake, Unity Catalog, pipelines, workflows) and MongoDB (schema design, performance tuning, Atlas)
- 5+ years of experience partnering with business, product, data, security, and compliance stakeholders to deliver outcomes-driven solutions
- 4+ years of people leadership experience, including mentoring senior engineers and building high-performing teams
- Demonstrated experience embedding AI or intelligent automation into modernized enterprise workflows, with awareness of responsible AI, security, and governance considerations
Preferred Qualifications:- Azure certifications (Solutions Architect, DevOps Engineer) and/or Databricks certifications
- Hands-on experience with AI-assisted development tooling and modern AI platforms (LLMs, agent frameworks, vector databases)
- Experience in healthcare, PBM
- Experience with mainframe or legacy platform modernization (COBOL, DB2, AS/400) to modern cloud stacks
*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $134,600 - $230,800 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
