Senior Data Analyst - Marketing

Supabase; United States; Remote; USD 120,000 - 170,000; Full time

Benefits offered by this job

Fully Remote

ESOP

Tech Allowance

Health Benefits

Annual Off-Sites

Flexible Work

Professional Development

Job summary

Supabase is seeking a Senior Data Analyst, Marketing to build measurement foundations across paid and PLG channels. You’ll partner with Marketing, Growth, and channel owners to move beyond vanity metrics toward causal insights that drive pipeline and revenue.

In this role, you’ll own marketing measurement strategy, design incrementality tests, and develop MMM-based forecasts. You’ll apply SQL and Python/R, enable self-serve analytics, and promote an AI-forward analytics culture across a fully

Qualifications

• 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 MMM, and how they complement each other.
• Advanced in SQL and at least one programming language (Python or R) for experiment analysis and modeling.
• Hands-on experience designing, running, and interpreting experiments across digital marketing channels.
• Experience building MMM and/or advanced attribution models, ideally in a consumption or BaaS environment.
• Strong business acumen and fluency in growth metrics: CAC, LTV, payback period, conversion rates.
• Think in terms of self-service and scale: build tools and frameworks for marketing teams to operate independently.
• Hold both technical and strategic context and discuss budget tradeoffs.
• AI-forward approach using LLMs and AI tooling in daily work.
• Clear communication to non-technical stakeholders and explain causal nuance in business terms.
• Thrive in async, autonomous environments and building a measurement function from the ground up.
• Nice to have: experience in BaaS/open source dev tools; applied econometrics/time-series; familiarity with marketing tools.

Responsibilities

• Own 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.
• Translate complex measurement outputs into recommendations on where to invest, cut, and hit pipeline, revenue, and efficiency targets.
• Serve as the subject matter expert for marketing measurement, educating stakeholders on causality and model uncertainty.
• Design and run always-on incrementality tests, user- and geo-level, to quantify the causal impact of key channels.
• Calculate incremental lift, incrementality percent, and incremental ROAS/CPA to guide budget reallocation.
• Build repeatable analysis templates and playbooks for experiment design, analysis, and readouts.
• Partner with channel owners to build and prioritize an experimentation roadmap integrated into campaign planning.
• Build and maintain MMM to estimate channel contribution and optimal budget allocation.
• Incorporate seasonality, adstock, and saturation; validate with backtesting and reconciliation with experiments.
• Turn MMM insights into budget scenarios across channels and regions for non-technical stakeholders.
• Own context and tooling: metric definitions, model documentation, reusable patterns; promote AI-forward practices.
• Identify data gaps and work cross-functionally to fix root causes rather than patching downstream.

Skills

Marketing analytics

Data science

Experiment design

SQL

Python/R

Attribution modeling

MMM

Growth metrics

Communication

Tools

Google Ads

Meta

LinkedIn

Web analytics

CDPs

BI/Visualization tools

Job description

About Supabase

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.

About the Role

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.

This role is ideal for someone who thrives in async, fast-paced environments, is AI-forward in how they work, and is excited about building a measurement function from the ground up.

What You'll Be Responsible for

Marketing Measurement Strategy

• 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

Incrementality and Experimentation

• 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

• Partner with channel owners (paid search, paid social, lifecycle, website/SEO) to build and prioritize a experimentation roadmap, embedding it into campaign planning, creative testing, and audience strategy

Media Mix Modeling and Forecasting

• Build and maintain media mix models using historical data to estimate channel contribution, marginal returns, and optimal budget allocation

• Incorporate seasonality, adstock, and saturation effects, and continuously validate model performance through backtesting and reconciliation with experiment results

• Turn MMM insights into budget scenarios and forecasts across channels and regions, communicated in a way non-technical stakeholders can act on

Context, Tooling, and Data Integrity

• Own and build the context and skills that let marketing teams run accurate self-serve analytics: metric definitions, model documentation, and reusable analysis patterns, not just dashboards

• Use AI tools as a core part of daily work to accelerate analysis and go deeper than a traditional analyst workflow allows, and help establish AI-forward practices across the marketing org

• Identify gaps and inconsistencies in marketing data (tracking, spend, platform exports) and work cross-functionally to fix them at the root rather than patching around them downstream

You Might Be a Good Fit If You

• 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

• Are AI-forward in how you work: you use LLMs and AI tooling habitually and have a clear point of view on how it changes what an analyst can do

• Communicate clearly to non-technical stakeholders and know how to make causal nuance land in a business conversation

• Thrive in async, autonomous environments and are energized by building a measurement function from the ground up

Nice to Haves

• Experience in BaaS, DevRel or open source dev tool companies, connecting marketing spend to pipeline and revenue outcomes

• Experience with applied econometrics, time-series modeling, or Bayesian methods for MMM and experimentation

• Familiarity with common marketing and analytics tools (Google Ads, Meta, LinkedIn, web analytics, CDPs, BI/visualization tools)

What We Offer

• Fully Remote

  We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world.

• ESOP

  Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together.

• Tech Allowance

  Use this budget to set up your ideal work environment-laptop, monitor, headphones, or whatever helps you do your best work.

• Health Benefits

  Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us.

• Annual Off-Sites

  Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year.

• Flexible Work

  We operate asynchronously and trust you to manage your own time. You know what needs to be done and when.

• Professional Development

  Every team member receives an annual education allowance to spend on learning-courses, books, conferences, or anything that supports your growth.

About the Team

Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love.

• ~400 team members

• 60+ countries

• 20+ languages spoken

• Over $1B raised (including our $500M Series F)

• 540,000+ community members

We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support-not replace-existing tools and communities.