Data Analyst (product focused)

THE ROLE

We re seeking a product-focused analyst who will help the business find growth opportunities, explain performance, and support decision-making across Product and Marketing. The role is hands-on and broad: you will work on product and marketing analytics, KPI reporting, and measurement for new features and experiments. Work is prioritized by business impact and shipped iteratively.

You will also own the implementation behind your work: managing connection of sources, keeping ELT jobs healthy, building dbt models and marts, and maintaining consistent KPI definitions across dashboards and tools.

This is a 100% remote\/work-from-home role.

THE KEY RESPONSIBILITIES

• Identify growth opportunities and business problems, quantify impact, and help prioritize what to build next.
• Own analytics projects end-to-end: requirements implementation rollout stakeholder adoption.
• Build and expand KPI reporting: define missing metrics, create dashboards, and measure new feature impact
• Build and maintain the analytics stack: connect data sources, manage ELT\/pipelines, and develop dbt models\/marts.
• Investigate metric drops\/spikes, find root causes, and turn findings into actionable recommendations.
• Product marketing analytics: analyze funnels, activation\/retention, feature performance, plus acquisition channels, attribution, and campaign performance.
• Ensure data reliability by implementing tests, monitoring, and documentation.
• Support experimentation: partner with the Product team to design experiments, monitor results, and evaluate impact.

THE MUST-HAVES

• 3+ years in Product\/Data Analytics, Analytics Engineering, or a similar role (ideally B2C\/SaaS).
• Strong SQL and hands-on dbt (models, tests, docs).
• Python for analysis and automation.
• End-to-end data delivery skills: connect sources when needed, build production-ready pipelines, and design layered dbt models (staging, intermediate, marts).
• Product analytics fundamentals: funnels, cohorts, retention\/activation, segmentation, A\/B testing basics.
• Ownership mindset: you can take ambiguous requests, define success metrics, deliver a solution, and drive decisions.
• Engineering mindset: Git, code reviews, clean code, testing, and documentation.
• Strong stakeholder communication: align stakeholders, explain complex topics simply, and write clear documentation.
• Experience with BI tools (Looker\/Tableau\/Power BI\/Metabase or similar).