Senior Business Data Analyst - Remote

Optum is dedicated to improving health data flow to create a more connected healthcare system. They are seeking a Senior Business Data Analyst to define data requirements, conduct data analysis, and collaborate with data engineers to enhance data processes and quality management.

Responsibilities:

• Define, gather, and review data requirements for health insurer's Eligibility/Membership and Claims databases (e.g., Medical, Pharmacy Claims)
• Conduct data profiling and analysis to determine how source data can fulfill business and technical requirements
• Translate business needs into clear, actionable data functional specifications
• Collaborate with data engineers to create new repeatable data ETL processes and/ or update existing repeatable data ETL processes
• Design and perform QA checks ensuring development efforts align with expectations
• Author and maintain comprehensive documentation such as functional specifications, test plans, data flow diagrams, project plans, and data dictionaries
• Research and investigate root causes of data issues and recommend effective solutions
• Work with data engineering team to manage complex, high-volume production data processes with a focus on reliability and scalability
• Develop analyses and insights to assess and communicate code changes/updates to production processes to internal and external stakeholders

Requirements:

• 4+ years of hands-on data analysis of health insurer's medical eligibility/membership and medical claims data
• 4+ years of business analyst experience, gathering requirements and writing data functional specifications
• 4+ years of hands-on experience with database technologies such as Oracle, SQL Server, DB2, Teradata, Snowflake
• 4+ years of hands-on experience writing ad hoc SQL against a data warehouse that contains large volumes of data from a variety of different sources
• Intermediate hands-on experience writing SQL statements using the following commands in a relational database (e.g., select statements with filtering, linking multiple tables, aggregating, sorting, nesting, etc.)
• Demonstrated experience identifying, analyzing, and improving business processes through automation and advanced analytics, partnering with technology teams to reduce manual effort, improve data quality, and increase operational efficiency
• Intermediate experience with Microsoft Excel, including experience creating pivot tables and writing functions (e.g., SUM, VLOOKUP, CONCATENATE, etc.)
• Demonstrated awareness of when to appropriately escalate issues/risks
• Demonstrated ability to work independently to conduct data profiling and analysis and then summarize and present findings to others
• Demonstrated ability to collaborate with data engineers, actuarial staff, project leads and managers for data driven deliverables
• Demonstrated ability in conducting in-depth code and data reviews to validate the accuracy and reliability of output
• Demonstrated excellent communication skills, both written and verbal
• Experience supporting data production processes that refresh on a regular cadence
• Experience establishing database connections with query tools (e.g., Toad, Dbeaver, DBVisualizer, etc.)
• Proven advanced SQL skills
• Experience in Payment Integrity, Claims Adjudication, Claims Operations
• Proven solid analytical skills to assess the impact of upstream database modifications on downstream data integrity, performance, and business processes
• Demonstrated ability to proactively develop and recommend solutions to mitigate or resolve downstream effects to ensure continuity of business deliverables
• Demonstrated ability to analyze and interpret relational data structures to identify dependencies and relationships between database tables and fields
• Proven ability to leverage automation and analytics tools (e.g., workflow automation, low code/no code platforms, advanced SQL, or analytics tooling) to streamline recurring reporting, data preparation, or operational processes, with measurable business impact
• Hands on experience using AI enabled tools (e.g., Copilot class tools, generative AI, or advanced analytics techniques) to enhance data analysis, insight generation, decision support, or documentation-moving beyond ad hoc use to repeatable, scalable ways of working
• Demonstrated ability to evaluate, validate, and responsibly apply AI generated outputs, combining domain expertise and sound judgment to support data driven decision making and continuous improvement initiatives