Data Lead
Wonderschool
Salary undisclosed
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Description
About Wonderschool
Wonderschool's mission is to ensure every child has access to early education that helps them realize their full potential. We do this by helping providers - small business owners who run child care programs - start, operate, and grow their businesses with powerful software, coaching, and support. We also partner with governments to modernize the public child care system, including building the technology platform for a state agency responsible for licensing, subsidy, and provider data statewide.
We are a Series B company backed by Andreessen Horowitz, Goldman Sachs, Long Journey Ventures, and First Round Capital. The business is cash flow positive and expanding that position.
A core part of our strategy is using AI to automate how work gets done across the company. Our agents already operate across product, engineering, operations, and go-to-market. The bottleneck is no longer the agents. It is the data underneath them.
About the Role
We are hiring a Data Lead to build the data foundation the whole company runs on: our commercial product, our government platform, and the AI agents that coach and support providers at scale.
This is a deeply hands-on role. You will write SQL, ship models, load data, and debug pipelines yourself every day. You will own two things that are really one problem: a single, trusted model of our providers, children, and families, and the delivery of state-mandated data work (Data Hub integration, legacy migration, identity resolution) for our government partners.
You will use AI agents heavily to do this work. We run Claude Code, Hermes, and OpenClaw across the company, and we expect you to multiply your output with them. We stay small on purpose and hire only when the work demands it.
Get this right and every agent, dashboard, and coaching interaction gets smarter. This role reports directly to the CEO.
What You'll Do
- Build the canonical data model for providers, sites, children, and families across BigQuery, HubSpot, Stripe, and our product databases. One ID, one definition, one source of truth
- Structure our data so AI agents can read it and act on it: entity tables, snapshots, and pre-computed briefings that power provider coaching at scale
- Own data delivery for our state government platform: bi-directional Data Hub sync, historical licensing data migration, staging-to-prod loads, validation, and governance sign-off
- Lead identity resolution and deduplication across legacy state systems so every provider and child has one accurate record
- Define and document the metrics the business runs on, from "active provider" to churn risk, and make them self-serve for operations and provider success teams
- Set the data quality bar: monitoring, alerting, lineage, and handling of sensitive data in line with government agreements
- Use agents to automate your own workflows first, then help other teams do the same with their data questions
What Success Looks Like
- State data loads pass validation and acceptance without heroics
- Zero duplicate-provider incidents across our systems and the state's
- Anyone in the company can answer "how is this provider doing" in one query, and so can an agent
- Agents deliver accurate, personalized coaching to a pilot cohort of providers, validated by our provider success team
- Metrics stop being debated in meetings because definitions are documented and trusted
Who You Are
You have been the first or early data hire at a startup and you have also shipped data work in a regulated environment, govtech, healthtech, or fintech, where governance, masking, and audit trails are table stakes. You are as comfortable writing a dbt model as you are working through a data governance agreement with a state counterpart. You have real scar tissue from entity resolution and dedup work. You already use AI agents as a daily part of how you work, you understand what makes data legible to an LLM, and you figure things out independently. You are happiest as a team of one or two and would rather automate a task than hire around it. You want to build the system, not inherit one.
Location
- San Francisco, California - in-person, 5-6 days a week in our office in Rincon Hill
Why Join Us
- Founding data hire with direct access to the CEO and a mandate to build from zero
- Your work powers both a government platform serving a state's child care system and AI agents coaching thousands of small business owners
- Small, fast-moving team that values action over process
- Real data, real stakes: government agencies, child care providers, parents, and teachers all depend on what you build
About this role
Wonderschool is building software and platforms to help child care providers run their businesses and to modernize state child care systems. As Data Lead, you'd be the founding data hire responsible for creating the data foundation that powers both the commercial product and the company's AI agents—which are already operating across product, engineering, and go-to-market but are bottlenecked by data quality and structure.
The work is hands-on and spans two interconnected problems. You'll build a canonical data model across BigQuery, HubSpot, Stripe, and internal databases to create a single source of truth for providers, children, and families. You'll also own data delivery for government partners, including Data Hub integration, legacy system migration, identity resolution, and validation work that has real regulatory stakes. A significant part of how you'll multiply your own output is by using AI agents (Claude Code, Hermes, OpenClaw) to automate workflows, then helping other teams do the same. You report directly to the CEO.
This role demands someone who has been an early data hire at a startup and has also shipped data work in regulated environments—govtech, healthtech, or fintech—where governance, audit trails, and data masking are non-negotiable. You need real experience with entity resolution and deduplication, comfort writing SQL and dbt models, and the ability to work independently. You're someone who prefers to automate rather than hire, and you want to build systems from zero rather than inherit them. The position is in-office in San Francisco, 5–6 days a week.
How this employer is doing
solid
- Recently Raised Funding
- Recent Acquisition
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Pay for this role
The employer didn't post a pay range for this role. That usually means pay is set in negotiation, which favors whoever arrives with numbers. Check ranges on comparable Data Lead postings in San Francisco, and analyze any offer before you accept it.
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