Sales Data Analyst | SQL, BigQuery & Dashboards
Confirmed on the employer's own hiring board on Nov 8, 2026. First seen by Alion on Sep 21, 2026.
Are you a SQL-fluent analyst who can look at a raw BigQuery table and turn it into an answer a sales leader can act on the same day?
Are you someone who instinctively distrusts a number until you've traced exactly which model it came from and what grain it's sitting at?
Are you comfortable using AI tools like Claude Code every single day to write, debug, and ship SQL faster - not just someone who says they're "open to" AI?
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 waits for someone to ask a question before opening BigQuery.
We need someone who goes looking for the story in the data before anyone asks for it.
We are looking for a Sales Data Analyst who can specialize in the full sales side of the business: bundles, DTC order economics, subscriptions and churn, product profitability, and phone sales team performance.
In order to achieve this, you will work directly inside our dbt-modeled BigQuery gold layer, building dashboards from scratch in areas where none exist today - starting with bundle performance and phone sales optimization.
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 turning a messy transactional dataset into a number a sales leader trusts enough to act on...
If you want to be the person who finally builds the dashboards that don't exist yet, not maintain ones that already do...
If you're an AI-native analyst who moves noticeably faster because of it...
Then APPLY NOW!
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Results:
Dashboards and analyses that sales and ops leadership actually use to make calls - not reports that sit unread.
A real bundle-performance story (which tiers convert, where bundles cannibalize each other) built from data that already exists but has never been turned into an answer.
Subscription and churn reporting that correctly separates true churn from payments rescued through payment-retry recovery - not a naive rebill count.
Phone sales performance analysis that tells reps and managers exactly what separates the best performers from the rest.
A gold-layer query and dashboard footprint sales leadership can rely on without needing to check your work.
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Responsibilities:
Own SQL-based analysis across bundles, DTC order economics, subscriptions, churn, product profitability, and phone sales performance.
Build the first real bundle-performance dashboard from data that already exists in our BigQuery gold layer.
Build the first phone sales performance dashboard, using rep-level and funnel-level data.
Build the MRR waterfall (new, expansion, contraction, churn) and cohort retention views from scratch.
Correctly separate true churn from payments rescued through our payment-retry / involuntary-churn recovery flow.
Analyze order-line-level revenue, discounts, and reversals to explain margin swings before finance has to flag them.
Own unit-economics analysis by product and by cohort, incorporating COGS and commission.
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 which mart actually answers which question.
Build self-serve dashboards and saved queries so sales leadership can answer their own questions without pinging you for every cut of the data.
Work across our homegrown BI stack (Metabase, Looker Studio, and whatever else gets added) without needing months of ramp-up on a new tool.
Flag data-quality issues and anomalies before they reach sales or finance leadership.
Manage multiple concurrent analysis requests while maintaining accuracy and speed.
Provide regular updates on what you're finding, what's blocked, and what needs a decision.
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Requirements:
3+ years of hands-on SQL analysis against a real production warehouse (BigQuery strongly preferred), ideally against order, subscription, or payment data.
AI-native in practice: you can point to a real example of using Claude Code, Cursor, or similar to ship a SQL model or dashboard faster.
Comfortable working directly in a dbt-modeled gold layer - reading model lineage and understanding grain.
Experience analyzing subscription businesses: MRR movements, cohort retention, churn definitions, payment-retry/recovery flows.
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.
Experience with large, messy transactional datasets - order systems, payment processors, or subscription billing platforms. CheckoutChamp or Shopify experience is a plus but not required.
Strong written communication - comfortable explaining a nuanced number to a non-technical sales leader, and "trust me" isn't an answer we accept.
Highly organized, disciplined, and comfortable managing multiple concurrent analyses at once.
Strong figure-it-out ability - comfortable defining a metric before anyone hands you a spec for it.
Bachelor's degree in a quantitative field preferred, not required - equivalent hands-on experience is a real substitute, not a lesser one.
Experience working with CheckoutChamp, Aircall, or similar order/phone systems is advantageous.
Work 6 days/week.
Work 10 hours/day.
Read 2 books/month.
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Reward:
100% Remote, contract position.
You will report directly to our Data Team Lead, working across some of the most important sales 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!