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 repeatable operating practices that reduce manual effort and improve quality across the solution lifecycle.