Senior Product Analyst

Responsibilities

• Drive Strategic Product Insights: Conduct deep-dive cohort, funnel, and segmentation analyses to diagnose merchant churn, optimize activation paths, and map feature adoption profiles. Translate complex behavioral patterns into actionable recommendations that influence product prioritization and roadmap direction.
• Scale Analytics Through Governance: Establish clear intake workflows, project boundaries, and self-serve frameworks to scale analytics capabilities across product pods. Enable cross-functional stakeholders to answer baseline data questions independently via BI tools.
• Own Product Data Transformation (dbt): Partner with data engineering to design and maintain clean, performant data models in dbt. Transform raw event-tracking data (hardware telemetry, digital menu clicks, ticket processing strings) into structured, reusable tables (merchant health and feature adoption marts).
• Define Metrics & Champion Tracking Quality: Partner with product managers to define definitive success criteria and tracking requirements before new features launch. Collaborate with engineering to ensure instrumentation is accurate, audit pipelines for data gaps, and mitigate data debt.
• Define the Standards & Elevate the Team: Help define core metric frameworks and tracking standards. Mentor junior analysts, lead documentation or training efforts, and set a high bar for analytical rigor.

Requirements

• Strong SQL skills and proven experience using dbt to transform raw data into production-grade analytics tables inside a cloud data warehouse (e.g., Snowflake)
• Practical experience leveraging a modern data stack, specifically combining dbt with behavioral event tools (e.g., Heap) or flexible business intelligence platforms (e.g., Metabase)
• Active use of modern AI assistants to accelerate workflow (code generation, debugging, automated documentation) paired with a practical understanding of how data structures must be formatted to feed AI-driven application layers
• Strong grasp of how product metrics drive core business outcomes (retention, conversion, revenue). Ability to translate complex data into clear, contextual narratives that influence product strategy
• Proactive partner who thrives in ambiguity, confidently challenges assumptions with data, and works cleanly across product and engineering boundaries to solve problems
• 4+ years of progressive experience in product analytics, data analytics, or a related data field

Nice-to-Haves

• Experience in point-of-sales (POS), or the Food and Entertainment industry
• Experience with Python, Jinja, or reverse ETL workflows
• Experience developing and managing centralized semantic/metric layers or data catalogs optimized for LLM text-to-SQL utilities

Benefits

• Medical, Dental and Vision Insurance
• 401k with company match
• RSUs
• Paid vacation, 10 company holidays, sick time, and volunteer time off
• Employee Resource Groups
• Monthly cell phone and internet stipend
• Tuition reimbursement for up to $2,000 per calendar year