Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 12, 2026. UnitedHealth Group scores B on the Alion truth index.
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, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
The Data Architect is responsible for designing end-to-end Financial Data Mart from source ingestion and bronze-layer structures through silver-layer transformation and gold-layer business-ready data products for Optum Insight
This role provides hands-on architecture leadership across complex, multi-source data environments and establishes the data models, integration patterns, transformation logic, and SQL designs that Data Engineering teams implement.
The ideal candidate combines deep expertise in modern cloud data architecture with the ability to set technical direction, collaborate with engineering and business stakeholders, and translate complex Finance and business requirements into scalable, reusable data products.
Primary Responsibilities:
- Own the end-to-end architecture and design of enterprise data products, spanning ingestion, transformation, integration, modeling, and consumption
- Design data solutions across bronze, silver, and gold layers using modern medallion and lakehouse architecture principles
- Define how data from multiple source systems and tables is joined, transformed, standardized, and curated into business-ready data products
- Develop detailed logical and physical data models, source-to-target mappings, transformation rules, integration patterns, and complex SQL designs for Data Engineers to implement
- Partner closely with Data Engineers while maintaining clear accountability for what and how the data product should be architected
- Evaluate source-system structures, data relationships, grain, keys, dependencies, data quality requirements, and transformation complexity when developing architecture
- Apply the appropriate modeling technique based on business problems rather than relying on a prescriptive modeling methodology such as star schema
- Design scalable solutions on Databricks and Azure, or comparable modern cloud data platforms considered relevant
- Establish reusable architecture and data-modeling patterns that improve consistency, scalability, maintainability, and engineering velocity across data products
- Perform architecture and design reviews and provide technical guidance to Data Engineering teams
- Work with Product, Finance, Analytics, Engineering, and business stakeholders to translate business requirements into implementable data-product designs
- Identify architecture risks, data dependencies, integration challenges, and performance considerations early in the product lifecycle
- Serve as a senior technical leader capable of driving architecture decisions and resolving complex design issues across teams
- Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements
Required Qualifications:
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related discipline, or equivalent relevant professional experience
- 10+ years of experience in data architecture, data engineering, data modeling, data warehousing, business intelligence, or related enterprise data disciplines
- 5+ years of hands-on experience in data architecture and data modeling, including responsibility for designing solutions implemented by Data Engineering teams
- Solid experience designing end-to-end data products, from source ingestion through curated, consumption-ready data layers
- Experience architecting cloud data solutions on Microsoft Azure
- Experience working with large, complex enterprise datasets and integrating data across multiple operational systems
- Deep understanding of medallion architecture, including bronze, silver, and gold data layers
- Solid understanding of data modeling concepts, including relational, dimensional, normalized, denormalized, and domain-oriented approaches
- Solid understanding of ELT/ETL patterns, data pipelines, data quality, lineage, metadata, and data governance
- Advanced proficiency in SQL, including complex joins, transformations, aggregations, reconciliation, and multi-source data integration
- Demonstrated ability to design data solutions using Databricks; solid experience with Databricks or equivalent modern data platforms may also be considered
- Demonstrated ability to provide technical direction and design guidance to Data Engineers and other senior technical contributors
- Demonstrated excellent written and verbal communication skills with the ability to explain complex data architecture concepts to technical and non-technical stakeholders
Required Software & Technical Tools
The successful candidate should have solid hands-on architecture and design experience with modern enterprise data platforms and technologies, including:
- Cloud & Data Platforms
- Databricks: solid experience with Lakehouse architecture, Delta Lake, medallion architecture, Unity Catalog, and scalable data-product design
- Microsoft Azure: Experience architecting enterprise data solutions using Azure services
- Azure Data Lake Storage (ADLS Gen2): Experience designing cloud data-lake storage structures and ingestion patterns
- Azure Data Factory and/or equivalent orchestration technologies
- Experience with Apache Spark / PySpark concepts and distributed data processing
Preferred Qualifications:
- Experience designing data products supporting Finance, Accounting, Billing, Financial Reporting, or Financial Operations
- Healthcare industry experience is beneficial but not required
- Experience operating in large, highly regulated enterprise environments
- Experience with data governance, lineage, data quality, security, and enterprise architecture standards
- Understanding of enterprise financial data, including concepts such as general ledger, revenue, billing, accounts receivable/payable, financial hierarchies, or financial reporting
Leadership Expectations
This is a high technical-leadership role. The Data Architect is expected to set architecture direction rather than simply review designs produced by others.
The role should be comfortable moving between detailed data design and senior-level technical discussions, including reviewing SQL and data models, resolving cross-system integration decisions, guiding Data Engineers, and communicating architecture trade-offs to Product, Engineering, Finance, and business leaders.
Data Architecture & Modeling
- Advanced SQL skills, including complex joins, CTEs, window functions, transformations, aggregations, reconciliation logic, and performance considerations
- Solid knowledge of bronze, silver, and gold medallion architecture
- Data modeling across relational, dimensional, normalized, denormalized, and domain-oriented models
- Ability to define logical and physical data models, data-product structures, source-to-target mappings, data contracts, transformation rules, and integration patterns
- Experience designing solutions involving multiple source systems, complex relationships, large data volumes, and historical data
- Familiarity with data modeling tools such as ER/Studio, ERwin, Lucidchart, Visio, or equivalent
Engineering & DevOps
- Working knowledge of Git and modern source-control practices
- Familiarity with Azure DevOps and/or GitHub for version control, CI/CD, deployment, and engineering collaboration
- Understanding of Infrastructure-as-Code, automated deployments, and DataOps/DevOps practices is preferred
- Ability to review and provide architecture guidance on SQL, notebooks, data pipelines, and engineering implementation
Data Governance & Quality
- Understanding of metadata management, data lineage, data catalogs, data classification, access controls, and data-quality frameworks
- Experience with Databricks Unity Catalog, Microsoft Purview, or comparable governance/catalog platforms preferred
- Understanding of data privacy, security, retention, and regulatory requirements within large enterprise environments
Domain Knowledge
- Finance domain experience
- Candidates should ideally demonstrate experience designing enterprise data products supporting one or more of the following areas:
- General Ledger and financial accounting
- Revenue and revenue recognition
- Billing and Accounts Receivable
- Accounts Payable
- Financial Planning & Analysis (FP&A)
- Financial reporting and management reporting
- Cost and profitability analysis
- Financial close and reconciliation
- Chart of Accounts and financial hierarchies
- Customer, vendor, contract, and product master data
- Transactional and financial master/reference data
- Experience integrating financial data from platforms such as SAP S/4HANA, SAP ECC, Oracle ERP/eBusiness Suite, PeopleSoft, or comparable enterprise financial platforms is highly desirable
- Healthcare industry knowledge is a plus, particularly experience with healthcare financial, billing, claims, provider, member, clinical, or operational data
Leadership & Communication Skills
This role requires significant technical leadership, with responsibility for setting design direction for Data Engineers and influencing architecture decisions across teams.
The successful candidate will:
- Own architecture decisions for complex enterprise data products from ingestion through business consumption
- Provide clear technical direction to senior Data Engineers, developers, analysts, and other architects
- Lead architecture and design reviews and ensure engineering implementations align with approved designs
- Serve as the technical authority for complex data-modeling, integration, transformation, and architecture decisions
- Translate complex Finance and business requirements into scalable technical data designs
- Communicate architecture decisions, alternatives, risks, dependencies, and trade-offs effectively to both technical and executive stakeholders
- Influence across Product, Engineering, Analytics, Finance, Architecture, Security, and Data Governance organizations
- Facilitate technical discussions and drive teams toward decisions when multiple design approaches are available
- Challenge designs constructively and establish reusable architecture patterns rather than creating one-off solutions
- Mentor senior engineers and architects and help raise the organization's overall data architecture maturity
- Balance strategic architecture thinking with sufficient hands-on technical depth to examine SQL, data models, source structures, and transformation logic
- Operate effectively in a matrixed enterprise environment with multiple business and technology stakeholders
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

