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Homebase is seeking a Director of Data & AI to lead a 20+ person organization spanning Data Engineering, Data & ML Platform, Data Science, and Applied AI teams. This is a high-impact leadership role at the intersection of data strategy and AI product development.
Key responsibilities include:
- Own the Data & AI technical strategy and roadmap, aligning data engineering, data platform, data science, and applied AI initiatives with Homebase's product and business goals.
- Lead and grow a 20+ person organization, managing managers and senior individual contributors across four sub-teams. Recruit, develop, and retain top talent while building a culture of velocity, ownership, and craft excellence.
- Drive data platform and infrastructure reliability, scalability, and governance using Databricks, Unity Catalog, Airflow, and dbt. Ensure data is a trusted, self-serve asset across the company.
- Accelerate applied AI and ML in product by partnering with Product and Engineering to ship AI-powered features—from LLM-based assistants to recommendation systems and intelligent automation. Own the MLOps lifecycle from experimentation to production.
- Build data science rigor through experimentation frameworks, guardrail metrics, and evaluation pipelines that drive confident product decisions. Ensure models are reliable, fair, and cost-effective.
- Champion AI fluency organization-wide by coaching leaders to enable their teams with AI tools and workflows. Drive adoption of AI-assisted development practices.
- Set governance and standards for data quality, model monitoring, data contracts, and responsible AI use across the organization.
- Partner cross-functionally with Product, Growth, GTM, Finance, and CX to understand data and AI needs and enable a hub-and-spoke model.
Required qualifications: 10+ years in data and/or AI/ML with at least 5 years leading teams of 8+ across data engineering, data science, or applied AI. Director-level leadership experience managing managers and building organizations at scale. Deep technical fluency across the modern data stack and applied ML/AI systems. Strong product instincts connecting data work to customer outcomes. AI-first mindset with hands-on experience shipping AI-powered products. Excellent cross-functional communication skills. Experience with modern data platforms (Databricks, Snowflake) and tools (Unity Catalog, Airflow, dbt, MLflow). Must be based in or willing to relocate to Toronto and committed to hybrid work (Tues/Weds in-office).
Bonus: Experience building data and AI orgs at SaaS or marketplace companies serving SMBs, data-as-a-product disciplines, and experimentation platforms at scale.
