Data Analyst

About Upheal

We’re on a mission to help mental health professionals find better balance. Our therapy-focused AI automates tasks, captures insights, and tracks outcomes for healthier clients. We're committed to privacy, reducing burnout, strengthening connections, and boosting incomes.

About the role

Own the analytics layer that turns Upheal's product, billing, marketing and growth data into decisions. This role sits between Product, Growth, Business Analytics, and Engineering — you model the data, define the metrics, and answer the "what is actually happening and what should we do" questions for the company.

What you'll do

Build and maintain the analytics warehouse

• Develop and own dbt models on Redshift (sessions, subscriptions, billing, product engagement).
• Curate Snowplow event tracking — define new events, review Iglu schemas (incl. major-version bumps when fields change), and validate tracking implementations with FE engineers before they ship.
• Maintain Stripe and Snowplow-sourced subscription pipelines, and reconcile them against the source of truth (Stripe API, Superset, finance tooling).

Define and steward business metrics

• Own canonical definitions for product and revenue metrics — activation, engagement, conversion, MRR/ARR, churn, retention, etc. — and document the rules so the rest of the company uses them consistently.
• Build forecasting and scenario models to inform pricing and GTM decisions.
• User segmentation metrics — based on traffic source, business size, business opportunities, usage type, etc.

Answer business questions end-to-end

• Translate ambiguous asks from Product, Growth, Rev-ops, and Leadership into concrete analyses: scope the question, pull and model the data, deliver the answer with the caveats that matter.
• Build dashboards in Superset and PostHog; partner with stakeholders so the dashboards stay useful.
• Run ad-hoc deep dives: cohort analyses, funnel breakdowns, pricing experiments, billing edge-case investigations.

Cross-functional partnership

• Work with Engineering on instrumentation, schema changes, and data quality.
• Work with Business Analytics / Rev-ops on revenue recognition, billing reconciliation, and SaaS reporting.
• Work with Product and Growth team on feature impact measurement and user-segmentation work.

You should be comfortable with

• SQL at depth — window functions, CTEs, performance on a Redshift-scale warehouse; recognizing warehouse-specific syntax constraints.
• dbt — building, testing, and refactoring models; macros; understanding model lineage.
• BI tooling — Superset, PostHog, Tableau, Grafana, Grid or similar.
• Python — enough to maintain ETL scripts (e.g. Stripe API loaders) and do ad-hoc analysis where SQL isn't the right tool.
• Git workflow — branch / PR / review, working in a shared analytics monorepo.

Nice to have

• Billing & SaaS metrics — Stripe data model (customers, subscriptions, invoices, charges, payment methods); standard SaaS metrics (MRR, ARR).
• Event analytics — Snowplow or equivalent (Segment, Rudderstack); event schema design; PostHog or similar product analytics tools.
• Forecasting experience (cohort projections, scenario modeling) beyond reporting.
• Experience modeling pricing migrations or self-serve → subscription transitions.
• Familiarity with healthcare or therapy-adjacent product data (PHI handling, session-level analytics).
• Exposure to FE/BE codebases — enough TypeScript/React reading comprehension to trace where an event is fired from and review tracking PRs.

What "good" looks like in this role

• Stakeholders trust the numbers because the definitions are documented and consistent across surfaces.
• New product launches ship with tracking already designed and reviewed, not bolted on after.
• Rev-ops and Product disagree about a metric → you're the person who resolves it with data, not opinions.
• Business decisions (pricing, packaging, GTM) get a quantitative answer before they're made, not after.

What We Offer

• A mission-driven team passionate about supporting therapists and improving mental healthcare.
• Remote-first culture with flexibility and autonomy.
• Competitive compensation, equity, and growth opportunities.