Head of Data

Accountabilities

• Own the data strategy and roadmap, prioritizing initiatives according to their expected impact on revenue, costs, risk, and operational performance.

• Establish clear processes for intake, evaluation, and prioritization of data requests, communicating trade-offs, capacity, and priorities to leadership and the team.

• Lead the development and maintenance of the data warehouse, pipelines, and transformation models, including Google Cloud Platform, BigQuery, Dataform, and associated ingestion tools.

• Oversee dashboards, reporting infrastructure, and analytical solutions that help teams make informed, data-driven decisions.

• Develop and maintain reliable measurement and attribution capabilities, including in-house attribution models, incrementality testing, and server-side conversion tracking in collaboration with Marketing.

• Ensure customer segmentation, lifecycle analytics, and email performance analysis support customer retention and revenue growth.

• Establish robust data quality controls to identify inconsistencies and prevent inaccurate information from reaching reports, dashboards, and business decisions.

• Implement data access policies and governance frameworks that protect sensitive customer information and define appropriate permissions for employees and AI agents.

• Partner with Finance to reconcile orders and revenue across e-commerce, ERP, and financial systems while improving inventory aging analysis, demand planning, and reporting consistency.

• Evaluate the data technology stack, making defensible build-versus-buy decisions and consolidating or eliminating tools where doing so improves cost efficiency and operational performance.

• Establish a trusted semantic layer and certified business metrics so that dashboards, analysts, and internal AI-powered data tools use consistent definitions and reliable figures.

• Work closely with the CEO and senior leadership to translate analytical findings into clear recommendations that influence revenue, spending, and cost decisions.

• Lead and develop a small team spanning analytics, data engineering, and analysis, while remaining actively involved in SQL, data modeling, code review, and technical problem-solving.

• Integrate AI-assisted development tools into daily workflows, maintaining appropriate review processes, security controls, and safeguards for production data.

Requirements:

• At least eight years of experience in data or analytics, including three or more years leading a data function or team.

• Recent hands-on experience writing SQL and working with a modern cloud data warehouse within the past two years.

• Proven experience building data models using dbt, Dataform, or a comparable transformation framework, along with developing and maintaining data pipelines.

• Regular, practical use of AI tools in data work, including AI-assisted coding and code review, supported by appropriate quality checks and access controls.

• Demonstrated ability to influence business decisions related to revenue, profitability, or costs, with measurable outcomes that can be clearly explained and quantified.

• Experience making strategic build-versus-buy decisions and reducing technology or infrastructure costs with demonstrable savings.

• Strong executive communication skills, including the ability to manage stakeholder expectations, explain trade-offs, and align data initiatives with business priorities.

• Ability to turn complex analyses into concise recommendations, clear visualizations, and actionable insights that leadership can use.

• Broad technical versatility across analytics, experimentation, attribution, reporting, data infrastructure, and governance.

• Strong analytical reasoning and a first-principles approach to unfamiliar problems, with the ability to challenge assumptions and identify practical solutions.

• A hands-on leadership style, combining team development and strategic direction with direct technical contribution.

• Nice to have:Experience in regulated industries such as hemp, cannabis, alcohol, or supplements, particularly where advertising, tracking, and attribution are affected by regulatory constraints.

• Nice to have:Experience in e-commerce, direct-to-consumer (DTC), or other consumer-focused businesses.

• Nice to have:Familiarity with Shopify event tracking, particularly for headless storefronts.

• Nice to have:Experience with identity resolution, marketing attribution, marketing mix modeling (MMM), or incrementality testing.

• Nice to have:Experience with semantic-layer technologies such as Cube and cloud platforms such as Google Cloud Platform.

• Nice to have:Experience working with Finance data, including revenue reconciliation, inventory management, and demand planning.

Benefits:

• Base salary:Annual range of$150,000–$250,000 USD.

• Remote work:Remote position within the United States, with a preference for candidates based in New York, San Francisco, or Los Angeles.

• Leadership opportunity:Own the data function end to end and shape its strategy, infrastructure, governance, and operating model.

• Business impact:Directly influence revenue growth, profitability, marketing investment, inventory planning, and operational efficiency.

• Technical ownership:Opportunity to shape the data technology stack, evaluate emerging AI tools, and make strategic build-versus-buy decisions.

• Cross-functional collaboration:Work closely with executive leadership, Finance, Marketing, Operations, and sales-channel teams.

• Team leadership:Lead a small, multidisciplinary data team while maintaining hands-on involvement in technical and analytical work.

• Innovation and autonomy:Help build scalable data capabilities in a growing business operating in a complex and evolving regulatory environment.