Head of Data

About Mood

Mood is a category-defining omni-channel hemp brand offering a full product suite across DTC online and retail partners. We are scaling fast and doing it profitably. We win through a premium product experience that brings best-in-class shopping to one of the most highly regulated industries. Our mission is simple: Enable access to premium hemp products of the highest quality, conveniently.

We are still early in our journey, and the right people can make a lasting impact. As we continue to grow and build new ventures, our data function supports an increasingly broad range of business needs.

We operate in a highly regulated and evolving environment. The rules around advertising, tracking, and selling can change quickly, and our data function must be able to adapt with them.

About the Role

As Head of Data, you'll own Mood's data function end to end. You'll lead the team while staying hands-on in the work, not just directing it.

Your job is to turn data into decisions that improve profitability. You'll prioritize work based on its impact on revenue, cost, and risk—and say no to the rest. You'll write and review SQL and models and work hands-on with AI tools, including AI coding tools, to operate with the leverage of a much larger team.

If you'd rather manage from a distance or solve most problems by adding people, this role won't suit you. If you want to own the whole function, keep your hands in the code, step up without being asked, and see your analysis change what the business does, it will.

What You'll Own

- Strategy & Roadmap: Determine what the team works on, in what order, and what it turns down. You'll establish how requests come in and get ranked and keep leadership and the team clear on priorities, tradeoffs, and capacity.
- Warehouse & Pipelines: Own BigQuery, Dataform models, and ingestion from the systems the business runs on.
- Reporting & Analytics: Own the dashboards and analysis teams use to make decisions.
- Measurement & Attribution: Own the in-house attribution model, incrementality tests, and the data behind server-side conversion tracking, built with Marketing and kept sound as the rules on tracking change.
- Data Quality: Catch bad data before it reaches a report or a decision.
- Access & Governance: Determine which people and AI agents can access which data, including sensitive customer data.

What Success Looks Like

First 90 Days

- You've ranked data initiatives by their revenue or cost impact and said no to work that falls below the line.
- Customer segmentation and lifecycle analytics, including email, are actively helping grow revenue from existing customers.
- Data is kept safe: access is tightly controlled, AI agents operate on production data within clear guardrails, and sensitive customer data receives the strictest handling.
- You understand what each tool in the data stack does, what it costs, and where it adds value—and you've made your first build-vs-buy decisions.

First 6 Months

- Marketing trusts the in-house attribution model, and incrementality tests are reliable enough to inform spend decisions.
- Orders and revenue reconcile across Shopify, the ERP, and Finance, while inventory aging and demand planning operate from the same trusted data.
- You've reduced the cost of the data stack by consolidating or removing tools where it makes financial and operational sense.
- Every team works from one trusted set of numbers: certified metrics in the semantic layer used consistently across dashboards, analysts, and our internal data bot.

What You'll Work With

- Cloud & Warehouse: Google Cloud, BigQuery
- Transformation: Dataform
- Semantic Layer: Cube
- Ingestion: Airbyte, dlt, Prefect
- Experimentation: Statsig
- Tracking: GA4, plus server-side tracking
- Business Systems: Shopify (headless), Klaviyo, Salesforce, Xoro (ERP)
- Reporting: Internal dashboards
- AI: Claude Code and an internal data bot that answers questions from certified queries

You'll decide what stays, what goes, and what gets built.

Who You'll Work With

- The Head of Finance , your manager, on reconciliation, inventory, demand planning, and the cost of the data stack.
- The CEO , on the revenue and cost decisions your work informs.
- Your team: a small team across analytics, data engineering, and analysis, plus specialist contractors.
- Teams across the business that rely on the numbers, including Marketing, Operations, and each sales channel.

What You Bring

- 8+ years of experience in data or analytics, including 3+ years leading a data function or team .
- You've written SQL and worked hands-on in a modern cloud data warehouse within the last two years.
- You've built data models using dbt, Dataform, or a similar framework, as well as data pipelines.
- You use AI tools every day in your hands-on data work, including to write and review code, with appropriate review processes and access guardrails in place.
- You have a track record of data work that influenced revenue or cost decisions, and you can quantify the impact.
- You've made build-vs-buy decisions you can defend and significantly reduced tooling or infrastructure costs, with measurable savings.
- You manage up effectively and communicate clearly with executives.
- You turn complex analysis into clear charts and concise recommendations that leadership acts on.
- You can move easily between very different types of work, from attribution and experimentation to dashboards and data infrastructure.
- You reason through unfamiliar problems from first principles rather than relying on assumptions.
- You're comfortable leading a small team while remaining hands-on in the technical work.

Nice to Have

- Experience in a regulated industry such as hemp/cannabis, alcohol, or supplements, particularly with marketing attribution and tracking under regulatory constraints.
- Analytics experience in an e-commerce, DTC, or similar consumer business.
- Experience with Shopify event tracking, especially on a headless storefront.
- Experience with identity stitching, attribution, MMM, or incrementality testing.
- Experience with semantic layers such as Cube.
- Experience with Google Cloud Platform (GCP).
- Experience working with finance data, including reconciliation and inventory.

Location

Remote, with a preference for candidates located in New York, San Francisco, or Los Angeles .

Compensation

$150,000–$250,000 base salary

Legal Disclaimers

Equal Employment Opportunity (EEO)

Mood is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, sex, gender identity or expression, sexual orientation, age, disability, national origin, genetic information, veteran status, or any other protected category under applicable law. All employment is based on qualifications, merit, and business needs.

Americans with Disabilities Act (ADA)

Mood is committed to working with and providing reasonable accommodations to applicants with physical or mental disabilities. If you need a reasonable accommodation for any part of the employment process, please contact HR and let us know the nature of your request and your contact information.