Marketing Data Analyst

Are you a marketing analyst who trusts a platform's reported ROAS about as far as you can throw it — and knows exactly how to check it against reality? Are you comfortable untangling affiliate cost, ad spend, and funnel attribution across Meta, Google, and a contractual rate card, all in the same afternoon? Are you the kind of analyst who reaches for Claude Code or a text-to-SQL copilot before you'd ever write a query by hand from scratch? We are My Derma Dream! A nearly 9-figure Skin Care brand in the United States since 2022. We are continuing to scale quickly and hiring across multiple functions across the business. BUT… We do not need an analyst who reports whatever number a platform dashboard shows. We need someone who checks it against our own data before anyone else has to ask. We are looking for a Marketing Data Analyst who can specialize in affiliate marketing, paid media (Meta/Facebook, Google Ads, and other major platforms), funnel analysis, dropoff analysis, and traffic attribution. In order to achieve this, you will work directly inside our dbt-modeled BigQuery gold layer — reconciling three parallel ROAS definitions, and tracing affiliate cost back to our contractual rate cards instead of a self-reported number. You will use AI tools like Claude Code and text-to-SQL copilots daily to move faster than a traditional analyst workflow allows, and you'll work across our homegrown BI stack (Metabase, Looker Studio, and whatever else gets added) without needing months of ramp-up on a new tool. If you love the problem of figuring out which number is actually true when three sources disagree... If you want to be the person who finally fixes a UTM taxonomy everyone else has been working around... If you're an AI-native analyst who moves noticeably faster because of it...

Then APPLY NOW!

=========== Results: Affiliate cost and CPA analysis that leadership can trust because it's traced to the actual rate card, not just the affiliate network's own report.

Paid media analysis that catches a platform overstating its own conversions before it costs us budget.

A clear, defensible answer to "which ROAS number do we actually believe" across last-touch, aggregated, and first-touch attribution.

Funnel and dropoff analysis precise enough to tell us exactly where in the funnel we're losing people, not just that we are.

=========== Responsibilities: Own SQL-based analysis across affiliate marketing, paid media, funnel performance, and traffic attribution.

Trace affiliate cost to our contractual rate cards, using the affiliate network's own reporting only as a reconciliation check, never the source of truth.

Analyze spend, conversions, and ROAS across Meta/Facebook, Google Ads, and AppLovin.

Investigate and explain discrepancies between platform-reported conversions and our own verified order data.

Work fluently across three parallel ROAS definitions (last-touch, aggregated, first-touch) without ever averaging them together.

Analyze funnel-level dropoff using landing-page and session-level data to find exactly where we're losing people.

Help untangle funnel identity issues where a single ad account maps to multiple funnels.

Help define and enforce a real UTM taxonomy in place of today's inconsistent tagging.

Use AI tools such as Claude Code, Cursor, and text-to-SQL copilots daily to write, debug, and ship SQL and dashboards faster.

Work directly inside a dbt-modeled gold layer — understand model lineage and grain well enough to know when two similarly-named metrics are legitimately different, not a bug.

Build dashboards across our homegrown BI stack (Metabase, Looker Studio, and whatever else gets added).

Manage multiple concurrent analyses across channels while maintaining speed and accuracy.

Provide regular updates on what you're finding, what's blocked, and what needs a decision.

=========== Requirements: 3+ years of hands-on SQL analysis against a real production warehouse (BigQuery strongly preferred), ideally against ad-spend, funnel, or campaign data.

AI-native in practice: you can point to a real example of using Claude Code, Cursor, or similar to ship a dbt model or funnel dashboard faster.

Real hands-on experience with Meta/Facebook Ads reporting and at least one other major paid platform (Google Ads, TikTok, AppLovin, etc.).

Experience with affiliate marketing / performance marketing networks (Everflow, Impact, CJ, or similar) and CPA-based cost models.

Comfortable working directly in a dbt-modeled gold layer.

Funnel and conversion-rate analysis experience — landing pages, advertorials, order-form flows, and the tracking (UTM, click IDs, session data) that ties traffic to outcomes.

Comfortable across a homegrown, evolving BI stack (Metabase, Looker Studio, and more as it's added), including building one-off dashboards yourself using Claude Code.

Strong written communication — comfortable telling a marketing lead that a channel's reported number doesn't match reality, and making it land with evidence, not just an assertion.

Highly organized, disciplined, and comfortable managing multiple concurrent analyses across channels at once.

Strong figure-it-out ability.

Bachelor's degree in a quantitative field preferred, not required — equivalent hands-on experience is a real substitute, not a lesser one.

Experience with GA4's BigQuery export (not just the GA4 UI) is advantageous.

Work 6 days/week.

Work 10 hours/day.

Read 2 books/month.

=========== Reward: 100% Remote, contract position.

You will report directly to our Data Team Lead, working across some of the most important marketing spend decisions in a rapidly scaling business.

This is a role for someone who wants ownership of an entire analytical domain from day one, not a narrow ticket queue.

If you are looking for the ride of a lifetime, then APPLY NOW!