About The Role
The role bridges the gap between complex data infrastructure and strategic business execution, translating raw transactional and behavioral data into actionable operational insights. The candidate will collaborate closely with product, finance, and marketing teams to establish core KPIs, build reliable automated dashboards, and conduct deep-dive analyses that drive growth.
This position requires a blend of strong technical execution and business acumen. The successful candidate will not only write optimized SQL to model data but will also present clear, data-driven recommendations to cross-functional stakeholders to optimize operations and product features.
Key Responsibilities
- Write complex, optimized SQL queries to extract, transform, and analyze large-scale datasets from cloud data warehouses like Snowflake or BigQuery
- Design, build, and maintain production-ready dashboards and reporting suites using visualization tools such as Tableau, Looker, or Power BI
- Partner with data engineering to define data requirements, schema designs, and build dbt models that power clean reporting layers
- Perform exploratory data analysis and cohort analyses to identify user behavior trends, product adoption bottlenecks, and operational inefficiencies
- Design and analyze A/B tests to measure the impact of new product features and marketing campaigns, presenting statistical outcomes to leadership
- Document data definitions, metric logic, and dashboard schemas to maintain a single source of truth across business units
What We Are Looking For
- 2–4 years of experience in a quantitative data analyst or business intelligence role, preferably within a fast-paced technology environment
- Expert-level SQL skills, including window functions, complex joins, query optimization, and CTEs
- Hands-on experience building interactive dashboards and semantic layers in Looker (LookML) or Tableau
- Solid understanding of statistical concepts, including hypothesis testing, sample size calculation, and regression analysis
- Bachelor's degree in a quantitative field such as Statistics, Economics, Computer Science, Finance, or a related discipline
- Bonus: Experience with dbt (data build tool), basic scripting in Python or R, and working knowledge of git version control
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Business Data Analyst
Scale.jobs
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