Data Analyst

Responsibilities

• Partner regularly with Marketing, Sales, Finance and Product teams. Learn their goals, their metrics, and the decisions they're actually stuck on.
• Own analysis end to end: clarify the real question, build or pick the right dataset, deliver the answer, and make sure a decision follows.
• Go deep on our subscription domain, then write it down. Metric definitions, caveats, always-filters, known gotchas. Domain knowledge that only lives in your head doesn't scale, and scaling it is the point of this role.
• Build analytics assets people trust without asking you first: models in dbt, explores in LookML, dashboards that hold up.
• Use our agent tooling as a force multiplier and contribute back to it. Feed it semantic context, flag wrong answers, harden the definitions it depends on.
• Contribute to the data platform where it unblocks you. Small model and pipeline improvements, debugging discrepancies, helping out when something breaks.
• Translate in both directions: business context into robust analysis, data reality into language a non-technical stakeholder can act on.

Languages