Data Analyst

What You'll Do Data Foundations

Build and own our core datasets: model data across HubSpot, PostHog, our platform, and financial and operational sources into clean, documented tables everyone can rely on.

Own data quality end to end: instrument new processes so they're measurable from day one, and find and fix the breaks before someone else finds them in a board deck.

Document metrics, definitions, sources, and methods so numbers mean the same thing to everyone and analyses are reproducible.

Reduce the cost of every future question by leaving the data model better than you found it.

Analysis

Do the analysis, not just the plumbing: funnel conversion by market and channel, install throughput and cycle times, capacity utilization, cohort behavior, and unit economics.

Get to root cause. When a number moves, you dig through the layers (data, process, and people) until you understand and communicate why.

Support experiment and program measurement, partnering with Growth and Sales on what actually moved the outcome.

Deliver clear, decision-ready findings with quantified impact, not just charts.

Enablement & Tooling

Make the business self-serve: build the reporting and tooling that answers recurring questions without a human in the loop.

Build durable tooling rather than one-off spreadsheets, so the work compounds instead of expiring.

Help teams ask better questions of the data, and be the person they trust when the number matters.

Leverage AI tools to compress the time between question, query, and answer.

What You Bring 3-6 years in data analytics, analytics engineering, or a similarly technical analytical role, ideally at a high-growth company.

Strong SQL. You write it daily, you can model data (not just query it), and you know why a number is wrong before someone tells you it is.

Real technical range: Python or R for analysis, comfort with version control, and the ability to build something durable rather than a one-off spreadsheet.

Business sense beyond the numbers: you understand how funnels, field operations, and customer experience actually work, and you pick the questions worth answering.

Strong communication skills: you can present findings to leadership, make a complex analysis feel simple, and land a recommendation.

Intellectual honesty: you report what the numbers say, including when they contradict the popular narrative or your own prior analysis.

You've AI-enabled yourself to move fast across whatever stack you land in.

Nice to Have

Experience in home services, energy, construction tech, marketplaces, or businesses with physical operations.

Experience building a data stack from an early stage (warehouse, transformation, BI) rather than inheriting one.

Experience with PostHog or other product analytics tooling.

Experience with job costing, project-based economics, or external partner reporting.