Senior IT Data Analyst

Responsibilities

• Analyze business and operational data needs
• Understand upstream and downstream data flows
• Translate business requirements into system and data requirements
• Convert business ask into system‑ready user stories when required
• Analyze enterprise data workflows and system dependencies to identify performance bottlenecks across applications and integration layers
• Define source‑to‑target data mappings, interface contracts, and end‑to‑end data lineage across upstream and downstream systems
• Supporting performance optimization by conducting data analysis, profiling, and validation using SQL
• Partnering with engineering teams to ensure system and data solutions meet performance, scalability, and operational requirements
• Performing impact analysis related to schema changes, integration logic updates, and data pipeline enhancements
• Leading backlog refinement sessions to ensure stories are clear, testable, and ready for sprint planning
• Supporting quarterly planning and backlog management for performance‑focused system and data initiatives
• Collaborating with Architecture, Data Engineering, and Application teams to align on data contracts, integration dependencies, and SLAs
• Identifying and managing risks and dependencies impacting application and data processing performance
• Supporting end‑to‑end testing to validate performance improvements and functional alignment with defined requirements

• Hands‑on experience with relational databases and SQL for data analysis, profiling, validation, and root cause analysis
• Strong understanding of data modeling concepts such as star and snowflake schemas, dimensions, and facts
• Experience collaborating with business stakeholders to gather and analyze business and functional requirements using structured artifacts such as BRDs, process flows, and data flow diagrams
• Ability to translate business goals into end‑to‑end system and data requirements including field‑level definitions, data rules, and non‑functional requirements
• Experience partnering with engineering teams to define and maintain source‑to‑target data mappings, interface contracts, and data lineage across integration layers
• Experience documenting and maintaining end‑to‑end data and process lineage across platforms such as Oracle, Snowflake, and S3 through operational workflows
• Ability to perform impact analysis related to upstream schema changes, data pipeline updates, and integration logic changes
• Experience performing cost‑benefit analysis to ensure technology investments are aligned with business objectives and deliver measurable value
• Ability to convert business requirements into actionable delivery plans with defined milestones and timelines for both system and data initiatives
• Experience identifying and managing risks and dependencies related to data workflows, system integrations, and processing pipelines
• Experience supporting delivery through quarterly planning and backlog management activities
• Experience managing product backlogs using tools such as JIRA, Confluence, Excel, and Share Point
• Ability to translate complex business and data requirements into user stories with clearly defined business value, acceptance criteria, and test conditions
• Experience leading refinement sessions to ensure user stories are implementation‑ready for sprint planning
• Ability to define story acceptance tests in collaboration with engineering teams using Acceptance Test Driven Development (ATDD) principles