DataOps - Lead Data Analyst at Cigna in United States Work Home

Job description

Job Description The Lead Data Analyst is responsible for translating business opportunities, customer needs, and operational challenges into actionable data requirements, integrated data solutions, and analytical deliverables. This role partners directly with business customers, Digital Product, Analytics, AI, Data Operations, and Technology teams to understand business processes, document requirements, assess data, validate solutions, and ensure delivered capabilities solve the intended business problem. The Lead Data Analyst serves as a key bridge between business stakeholders and the DataOps Engineering organization, providing hands-on expertise across business analysis, data profiling, solution validation, customer enablement, and process improvement so data and engineering investments align to measurable business outcomes. Key Responsibilities Business Engagement & Functional Analysis · Partner with business stakeholders to understand business objectives, operational processes, decision-making needs, and desired outcomes and how data supports them. · Facilitate discovery sessions, requirements workshops, and stakeholder interviews to translate customer needs into clear functional requirements, business rules, acceptance criteria, and value measures. · Ensure business context, intended use, process requirements, and expected outcomes are understood and documented before solution development begins. Data Analysis, Profiling & Requirements · Perform data discovery, profiling, and analysis to evaluate quality, completeness, metadata, usability, and fitness for purpose, identifying gaps and remediation needs early in the lifecycle. · Define and document business semantics, data definitions, transformation logic, source-to-target mappings, data relationships, and readiness criteria. · Develop clear functional and data requirements that enable efficient solution development. Data Product Integration & Validation · Partner closely with Data Operations and Data Engineering throughout design and delivery to ensure solutions reflect business intent and support reuse. · Develop analytical datasets, reusable data assets, and Gold layer data solutions when business requirements can be effectively addressed through analyst-led solution development. · Develop and execute functional testing, test cases, and business acceptance validation for engineered datasets, data products, and integrated solutions. · Coordinate customer feedback, user acceptance testing, adoption, and transition activities to ensure solutions are integrated successfully into business workflows. Business Process Automation & Optimization · Assess business processes to identify opportunities for workflow improvement, process simplification, and operational efficiency gains. · Identify opportunities where data, workflow automation, AI, or integrated solutions can improve business processes, operational efficiency, and customer outcomes. · Partner with automation, AI, DataOps, and Technology teams to define requirements, validate solutions, and measure realized business value when automation is appropriate. Solution Delivery & Customer Enablement · Develop analytical solutions, prototypes, and business insights when customer needs can be met effectively without extensive engineering investment. · Support rapid proof-of-concept and learning-stage work while establishing a clear pathway for solutions that require enterprise-scale operationalization. · Prepare documentation, training, and knowledge-transfer materials that enable customers to adopt and use data products, integrated solutions, and automated workflows effectively. Automation of the Analyst Function · Use AI, metadata, workflow, and reusable analytical patterns to improve requirements discovery, data profiling, documentation, testing, and traceability. · Develop reusable templates, requirements assets, testing approaches, and documentation standards that increase consistency and delivery speed. · Contribute to r