Own analytics for Commercial and Account Management use cases, including publisher performance, portfolio health, margin trends, pricing impact, product performance, and opportunity sizing.
Support Commercial, Pay/Risk, Marketing, and Finance teams with fast, high-quality analysis that helps diagnose trends, quantify impact, and drive business action.
Translate ambiguous business questions into structured analysis, clear recommendations, and decision-ready outputs.
Build and maintain trusted analytical datasets in dbt, helping define shared business logic and improve the quality of Coda’s Gold layer.
Help codify key metrics through semantic-layer tools such as LookML, the dbt semantic layer, or similar governed BI patterns.
Build dashboards in Tableau, Looker, and QuickSight that business teams actually use to monitor performance, identify issues, and make decisions.
Improve data quality and trust through dbt tests, freshness checks, anomaly detection, documentation, and root-cause analysis.

5+ years of experience as a Data Analyst, Analytics Engineer, BI Analyst, or similar role.
Strong SQL skills and experience working with large, complex datasets.
Strong business analytics experience, ideally in payments, fintech, eCommerce, gaming, digital commerce, marketplaces, or high-growth internet businesses.
Experience translating ambiguous business questions into structured analysis and clear recommendations.
Experience building dashboards in Tableau, Looker, QuickSight, Power BI, or similar tools.
Production experience with dbt, including models, tests, documentation, and reusable transformation patterns.
Familiarity with semantic-layer concepts such as LookML, dbt semantic layer, Cube, metrics layers, or governed BI models.
Working knowledge of AWS data tools such as Athena, S3, Glue, EMR, Redshift, or similar cloud data platforms.
Python skills for analytical work, especially pandas, numpy, and basic statistical analysis.
Strong understanding of business metrics such as TPV, revenue, gross profit, margin, conversion, retention, campaign performance, fraud/risk metrics, and account performance.
Strong written and verbal communication skills, especially with business and leadership stakeholders.
Ability to work independently, prioritize well, and move quickly in a fast-changing business environment.

Senior Data Analyst

Key skills