Optum, a global leader in healthcare technology, is seeking a skilled Databricks Architect to design and lead the development of enterprise data products. This role is crucial in transforming financial data from source ingestion through to business-ready data products, enhancing how millions access care and improve their health outcomes. Join a supportive and inclusive culture focused on innovation and professional growth, where your work directly impacts global health optimization.

This position owns the end-to-end architecture and design for enterprise data products, encompassing ingestion, transformation, integration, modeling, and consumption. You will establish data models, integration patterns, and transformation logic for complex, multi-source data environments using modern medallion and lakehouse architecture principles on platforms like Databricks and Azure. Responsibilities include developing detailed logical and physical data models, source-to-target mappings, and complex SQL designs for Data Engineering teams, while closely collaborating with stakeholders across Product, Finance, Analytics, and Engineering.

Key duties involve evaluating source system structures, defining data relationships, and applying appropriate modeling techniques. You will also establish reusable architecture patterns to enhance consistency, scalability, and maintainability across data products. This role demands active participation in architecture and design reviews, providing technical guidance, and identifying architecture risks and performance considerations early in the product lifecycle. Serving as a senior technical leader, you will drive architecture decisions and resolve complex design issues.

This role also entails staying compliant with company policies and directives, including those related to work location, team assignments, and flexible work arrangements. Collaboration with Data Engineers is essential, maintaining clear accountability for the architectural vision and implementation.

Candidates must possess a Bachelor's degree in a relevant field (Computer Science, Engineering, Information Systems, Data Science) or equivalent professional experience. A minimum of 10 years in data architecture, data engineering, or related disciplines is required, with at least 5 years focused on hands-on data architecture and modeling. Proven experience designing end-to-end cloud data solutions, particularly on Microsoft Azure, and working with large, complex enterprise datasets is essential.

Expertise in medallion architecture (bronze, silver, gold layers), data modeling concepts (relational, dimensional, normalized, denormalized), and ELT/ETL patterns is critical. Advanced proficiency in SQL for complex joins, transformations, and multi-source data integration is a must. Demonstrated ability to design data solutions using Databricks, including Lakehouse architecture, Delta Lake, and Unity Catalog, is required. Strong understanding of Apache Spark/PySpark concepts and distributed data processing is also necessary.

Excellent written and verbal communication skills are vital for explaining complex architecture concepts to diverse audiences. Experience with Databricks Unity Catalog, Azure Data Lake Storage (ADLS Gen2), and orchestration technologies like Azure Data Factory is highly beneficial. Familiarity with Git, Azure DevOps, and data governance principles is preferred. Experience in the Finance domain, supporting areas like general ledger, revenue recognition, or financial reporting, is a significant plus, as is any prior experience in the healthcare industry.