Head of Data

Responsibilities

• Lead Data Engineering, Data Science, Analytics, and Data Strategy as a unified organization.
• Partner with executives and Product to drive product strategy and define the data capabilities needed to support the roadmap.
• Own the strategic data asset and machine-learning roadmap, including pricing, lead scoring, propensity, and screening-risk use cases.
• Build the go-to-market data foundation, including unified customer profiles, segmentation, and journey tracking across Marketing, Sales, and Customer Success systems.
• Establish company-wide experimentation standards, from experiment design and success metrics through causal analysis.
• Directly manage Business Analysts and Data Scientists; review work and code quality, set analytical standards, prioritize requests, and guide project scoping.
• Own analytics self-service, semantic-layer improvements, and AI-powered tooling adoption across business, GTM, and Finance teams.
• Lead Data Engineering through the Data Engineering Manager, including warehouse architecture, pipeline priorities, cost, governance, and reliability.
• Scale the Data organization through hiring, coaching, career development, governance, and data-quality standards.
• Promote data literacy and insight adoption across Product, Engineering, GTM, and Finance.
• Represent Data to executives and the Board, translating forecasts, data requests, and OKRs into an executable roadmap.
• Own vendor and tooling strategy for the analytics stack.

Requirements

• 7+ years of experience in data, including 3+ years directly leading an Analytics or Data Science team.
• Experience hiring, reviewing work, and setting quality standards for data teams.
• Experience leading or partnering closely with Data Engineering, including warehouse architecture and pipeline priorities.
• Experience shipping and operating machine-learning features in production.
• Fluency with modern data-stack tools, including BigQuery or an equivalent warehouse, dbt or Dataform, and an experimentation platform.
• Hands-on SQL and Python proficiency sufficient to review team work.
• Experience partnering with Engineering, Product, Design, Finance, and executive stakeholders to drive data-informed strategy.
• Experience building or scaling self-service analytics while maintaining a single source of truth for metric definitions.
• Experience establishing data governance practices, including stewardship, quality monitoring, and access controls.
• Excellent communication skills for explaining technical topics to nontechnical audiences.
• Ability to balance strategic leadership with hands-on technical involvement.

Nice-to-haves

• Experience in B2B2C or platform/marketplace products.
• Background in fintech, proptech, real estate technology, or property/marketplace data.
• Experience governing an internal AI/LLM tooling layer.
• Experience managing globally distributed teams across the United States and Southeast Asia.

Compensation and Benefits

• Base salary: $250,000–$280,000.
• Equity participation.
• Medical, dental, and vision coverage from day one, with HSA/FSA options.
• Life and disability coverage and a SIMPLE IRA with company match.
• Flexible vacation, 11 holidays, and 3 recharge days.
• Parental leave, fertility benefits, legal benefits, and tax support.
• Business expense allowance, internet reimbursement, and Seattle transit support.