At Moxie, we empower ambitious aesthetic entrepreneurs to build profitable, independent practices—without burnout, overwhelm, or guesswork. In just a few years, we've grown from an idea to a global, remote-first team now supporting 700+ practices nationwide.
Our purpose is simple: to unlock sustainable success for aesthetic entrepreneurs, at every stage of their journey.
Staff Data Engineer
We're looking for a Staff Data Engineer to own Moxie's data infrastructure end to end: the pipelines (Prefect, Airbyte, Snowflake Openflow), the warehouse (Snowflake), and the modeling layer (dbt, Omni) that every number Moxie publishes depends on. Data and intelligence are Moxie's moat, and they are also where the gap between what we can do today and our full potential is widest. This is a highly visible seat on a small, ambitious team, and you close that gap.
Day to day, you'll partner with Engineering on production schema changes (Postgres to Snowflake), work with Finance to model accounting logic, build and maintain pipelines, and keep business-critical data available for internal teams and the practices we serve. Practice Intelligence and Practice 360 are built on this foundation, and you'll be the person who makes it solid.
Our Objectives for the Role
- Make every number Moxie publishes defensible: within six months the data stack is owned, alerted, lineage-mapped, and documented end to end, and "is the number right?" has a yes-answer for every priority metric flowing into Practice 360 decks, MBRs, Practice Intelligence reports, and Moxie Suite embedded reports
- Own the dbt and orchestration layers, maintaining and evolving Moxie's dbt models (including financial reporting logic such as cash vs. accrual basis and incentive calculations and their downstream effect on metrics like AOV) and taking over the Prefect and Snowflake Openflow orchestration layer along with the observability platform that monitors it
- Deliver one high-impact project in your first quarter by scoping and shipping either the accrual basis accounting data model (so dbt and Omni support both cash and accrual reporting as we move upmarket) or modelling historical EMR data to work with existing practice KPIs so owners can understand the performance of their business before/after joining Moxie; neither exists today
- Turn ad-hoc work into owned process by establishing the SOPs and KPIs the stack has been missing: a monthly Vanta security review, a scoping and execution process for production schema changes, a triage workflow from job and test failures to resolution, and monthly infrastructure KPIs for performance and cost
- Deepen the moat: by month nine you're proactively optimizing the stack (for example, Omni data refreshed every 15 minutes at predictable cost) and building the pipelines and models that move Practice Intelligence from descriptive to predictive to prescriptive, including safeguards for LLM-generated content in data products
We're Looking For
- 5-10 years of data engineering experience, with at least one stretch as an early data hire who took a system from "basics" to business-critical
- Deep dbt and SQL modeling skill applied to business logic: you've owned a dbt project of real complexity and can model financial concepts like cash vs. accrual accounting, incentive logic, and revenue definitions, and explain how a change upstream ripples through every downstream metric
- Python and software engineering fundamentals strong enough to own orchestration: you've run production pipelines on Prefect, Airflow, Dagster, or similar, handled schema evolution from an operational database into a warehouse, and set up alerting and observability so failures are caught before stakeholders notice
- A track record of leading end-to-end delivery: you gather requirements from non-technical partners (Finance, Product, Sales), scope the work, make the architectural call, ship it, and can articulate the tradeoffs you chose and the business value that resulted
- An ownership mindset about uptime, reliability, and cost; you treat data infrastructure as a living system that needs a steward, and SLAs, runbooks, KPIs, and cost optimization are things you build rather than wait to be asked for
- Fluency with AI tooling in daily work (Claude Code, Cursor, n8n, or similar) and a point of view on where LLMs belong in a data stack and where they need guardrails
- Someone who sees a data team as a driver of business outcomes, not a ticketing service; if "taking tickets from a queue" describes your ideal job, this won't be a fit
Why Join Us?
- You set the standard, not inherit one: as the second internal data hire on a small, ambitious team, your data patterns, conventions, and engineering philosophy become Moxie's
- A data architecture competitors can't match: Moxie's vertical model captures clinical events (Service Menu Item x Service Type x Service Product) tied to appointments, providers, and patients, and every additional service we sell makes the dataset richer
- A modern stack with room to grow (Snowflake, dbt, Omni, Airbyte, Prefect, GitHub) with AI tooling built into the workflow, and a tight Product and Engineering partnership so you see how the data you model changes what practices can do
- A highly visible IC role executing C-Suite level initiatives, with real input on the data roadmap and your own career trajectory
At Moxie, we believe in creating a workplace where everyone feels valued, trusted, and included. Our team lives by our values: act as owners, give more than we take, move with speed and care, and simplify and learn every day.
We welcome people of all backgrounds, experiences, and perspectives to apply. If you require any accommodations to fully participate in the interview process, please let us know, we’re happy to assist.
Compensation: $78,000 - $209,000
