Data Analyst Role

Data Analysts translate operational data into actionable insights. You will work with stakeholders to define metrics, acquire and reconcile data, investigate discrepancies, and transform recurring questions into analyses, reports, semantic models, and dashboards that stakeholders can use.

The role blends SQL, spreadsheets, scripting, and business intelligence tools with rigorous domain reasoning. You will profile and clean data, define calculations, identify trends and exceptions, validate results against source systems, and present findings in clear language tailored to decision-makers.

What you'll build - Recurring reports and dashboards with documented measures, refresh schedules, filters, alerts, and access controls. - Clean analytical datasets and semantic models that reconcile source fields, business definitions, relationships, and calculation logic. - Queries, scripts, and repeatable workflows that replace manual reporting and simplify testing and review. - Analyses such as variance, trend, cohort, performance, financial, program, or operational insights to identify changes and investigation areas. - Data-quality checks, reconciliation reports, issue logs, and documentation that establish data provenance and fitness for use.

Who you are You are precise with numbers and curious about what sits behind them. An unexplained variance is an invitation to trace definitions, filters, timing, and source records until the result makes sense. You can shift between a stakeholder's question and the data needed to answer it, communicate clearly, design for us

Data Analyst Role

Data Analysts translate operational data into actionable insights. You will work with stakeholders to define metrics, acquire and reconcile data, investigate discrepancies, and transform recurring questions into analyses, reports, semantic models, and dashboards that stakeholders can use.

The role blends SQL, spreadsheets, scripting, and business intelligence tools with rigorous domain reasoning. You will profile and clean data, define calculations, identify trends and exceptions, validate results against source systems, and present findings in clear language tailored to decision-makers.

What you'll build - Recurring reports and dashboards with documented measures, refresh schedules, filters, alerts, and access controls. - Clean analytical datasets and semantic models that reconcile source fields, business definitions, relationships, and calculation logic. - Queries, scripts, and repeatable workflows that replace manual reporting and simplify testing and review. - Analyses such as variance, trend, cohort, performance, financial, program, or operational insights to identify changes and investigation areas. - Data-quality checks, reconciliation reports, issue logs, and documentation that establish data provenance and fitness for use.

Who you are You are precise with numbers and curious about what sits behind them. An unexplained variance is an invitation to trace definitions, filters, timing, and source records until the result makes sense. You can shift between a stakeholder's question and the data needed to answer it, communicate clearly, design for us