Key Responsibilities • Lead and execute complex, high-stakes analyses — deep-dive investigations, statistical modelling, and multi-source data problems that require real technical depth, not just query-writing
• Guide and unblock the team on difficult technical problems: query optimization, data modeling challenges, messy/ambiguous datasets, and edge cases junior analysts get stuck on
• Write advanced, performant SQL against large and complex datasets (multi-table joins, window functions, query optimization, working with messy or poorly documented schemas)
• Build and maintain robust data models and pipelines in partnership with Data Engineering, and know enough about the underlying infrastructure to reason about data quality issues at the source
• Apply statistical methods (experimentation/A-B testing, regression, cohort and trend analysis) to move beyond surface-level reporting into rigorous, defensible conclusions
• Design and build dashboards and reporting frameworks, but also know when a dashboard isn’t enough and a deeper custom analysis is needed
• Set and enforce technical standards for the team — code review, data quality checks, analytical rigor, and documentation
• Mentor analysts by working alongside them on hard problems, not just reviewing finished output
• Translate ambiguous, loosely-defined business questions into structured, technically sound analytical approaches
• Present complex findings to senior stakeholders in a way that’s rigorous but accessible
• Own the technical roadmap for the analytics function’s tools, data models, and processes