Senior Data Analyst - Marketing

Job description

About this role

Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. We're looking for a Senior Data Analyst, Marketing to join our Data Intelligence team and build the measurement foundation that tells us what's actually working across paid and PLG channels. You'll work closely with Marketing, Growth, and channel owners, helping us move past platform-reported metrics and vanity numbers into causal, trusted answers about what drives pipeline and revenue.

Responsibilities

• Own the end-to-end marketing measurement strategy across experimentation, media mix modeling, and attribution for paid and PLG channels
• Establish and evolve the attribution framework: how platform data, multi-touch attribution, MMM, and experiments work together to inform decisions
• Translate complex measurement outputs into clear recommendations on where to invest, what to cut, and how to hit pipeline, revenue, and efficiency targets (CAC, payback, LTV to CAC)
• Serve as the subject matter expert for marketing measurement, educating stakeholders on causality, model uncertainty, and the limitations of platform-reported metrics
• Design and run always-on incrementality tests, user-level and geo-level, to quantify the causal impact of key channels, campaigns, and tactics
• Calculate incremental lift, incrementality percent, and incremental ROAS/CPA, and use these to guide budget reallocation
• Build repeatable analysis templates and playbooks for experiment design, analysis, and readouts so results are consistent across teams

Qualifications and requirements

• Have 6+ years in marketing analytics, data science, or a related role, with a focus on performance marketing and/or PLG growth
• Deeply understand marketing attribution, incrementality testing, and media mix modeling, and how they complement each other rather than compete
• Are advanced in SQL and at least one statistical programming language (Python or R) for experiment analysis and modeling
• Have hands-on experience designing, running, and interpreting experiments across digital marketing channels: search, social, display, email, in-product
• Have built or worked closely with MMM and/or advanced attribution models, ideally in a consumption or BaaS environment
• Have strong business acumen and fluency in growth metrics: CAC, LTV, payback period, conversion rates, funnel performance
• Think in terms of self-service and scale: your instinct is to build tools and frameworks that make marketing teams independently capable, not to become the bottleneck for every "did this work" question
• Can hold technical and strategic context at once: you're as comfortable in a model's residuals as you are in a conversation about budget tradeoffs