Director, Data & AI

About the role

You will own the end-to-end strategy and execution for the Data & AI organization at Homebase, guiding how data and machine learning become core competitive advantages. You will define the technical vision for a trusted, self-serve data platform and shape the roadmap for production ML and AI-powered product experiences. You will lead a 20+ person team spanning Data Engineering, Data & ML Platform, Data Science, and Applied AI with a focus on velocity, ownership, and craft excellence. You will partner directly with Product, Engineering, and GTM leadership to ensure data and AI capabilities drive measurable customer outcomes and business growth. This role requires you to build and retain a high-performing team while establishing governance, standards, and reliability for data and AI across the company. You will champion AI fluency by coaching leaders and enabling the broader organization to leverage AI tools and workflows effectively. Ultimately, you will ensure that data and AI are used responsibly and effectively to accelerate Homebase's mission of helping small businesses thrive.

Key facts

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Location: Canada

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Engagement: Full-time

What you'll do

• Own the Data & AI strategy and define the technical roadmap for data engineering, data platform, data science, and applied AI at Homebase.
• Lead and grow a 20+ person organization, managing managers and senior ICs across four sub-teams while recruiting, developing, and retaining top talent.
• Drive the reliability, scalability, and governance of Homebase's data stack, including Databricks, Unity Catalog, Airflow, and dbt, to ensure data is a trusted, self-serve asset.
• Accelerate applied AI and ML in product by partnering with Product and Engineering to ship AI-powered features such as LLM-based assistants, recommendation systems, and intelligent automation.
• Drive data science rigor by building experimentation frameworks, guardrail metrics, and evaluation pipelines that enable confident, data-driven product decisions.
• Champion AI fluency organization-wide by coaching leaders and teams on AI tools and workflows, including agentic coding and AI-augmented analytics, while measuring and sharing impact.
• Set governance and standards for data quality, model monitoring, data contracts, and responsible AI use, establishing yourself as the authority on data architecture and AI governance.
• Partner cross-functionally with Product, Growth, GTM, Finance, and CX to understand their data and AI needs and enable a hub-and-spoke model that empowers the entire organization.
• Build and maintain strong product instincts, connecting data and AI initiatives to customer outcomes and business metrics rather than only technical milestones.
• Maintain an AI-first mindset by actively using AI to improve your own workflows and staying current on frontier developments such as LLMs, agentic systems, and multimodal AI.
• Ensure excellent communication by translating complex technical concepts for non-technical stakeholders and building trust across the organization.
• Leverage modern data platforms like Databricks, Snowflake, or similar, with familiarity toward Unity Catalog, Airflow, dbt, and ML platforms such as MLflow, Baseten, or equivalent tools.
• Commit to a hybrid work model based in or willing to relocate to the Toronto area, with energized in-person collaboration on Tuesdays and Wednesdays at the Toronto hub.
• Demonstrate 10+ years of experience in data and/or AI/ML, with at least 5 years leading teams of 8+ across data engineering, data science, or applied AI.
• Bring Director-level leadership experience managing managers and driving technical strategy at companies with real scale.
• Show deep technical fluency across the modern data stack, including warehousing, orchestration, transformation, BI, and applied ML/AI production systems.
• Prove strong product instincts and the ability to connect data and AI work to customer outcomes and business metrics.
• Exhibit an AI-first mindset with hands-on experience using AI to enhance your workflows and leading teams that ship AI-powered products.
• Communicate effectively with both technical and non-technical audiences to build trust and alignment across the organization.
• Have substantial experience with modern data platforms such as Databricks, Snowflake, or similar, and familiarity with Unity Catalog, Airflow, dbt, and ML platforms.
• Commit to a hybrid work arrangement based in or willing to relocate to Toronto, with regular in-person presence on Tuesdays and Wednesdays.

Requirements

• 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 driving technical strategy at a company with real scale.
• Deep technical fluency across the modern data stack (warehousing, orchestration, transformation, BI) and applied ML/AI (production ML systems, LLMs, experimentation platforms).
• Strong product instincts connecting data and AI work to customer outcomes and business metrics.
• AI-first mindset with experience using AI to improve workflows and leading teams that ship AI-powered products.
• Excellent communication translating complex technical concepts for non-technical stakeholders.
• Experience with modern data platforms such as Databricks, Snowflake, or similar, and familiarity with Unity Catalog, Airflow, dbt, and ML platforms (MLflow, Baseten, or equivalent).
• Hybrid commitment: based in or willing to relocate to Toronto, with energized in-person collaboration on Tuesdays and Wednesdays.
• Experience building data and AI orgs at a SaaS or marketplace company serving SMBs.
• Background in establishing data-as-a-product disciplines (data contracts, semantic layers, data mesh concepts).
• Experience with experimentation platforms and causal inference at scale.

AI Fluency

We're an AI-first company. That's not a buzzword here - it's how we build. At the Director level, you are expected to:

• Push the boundaries of what's possible with AI across the organization, from production ML systems to agentic workflows, and lead a high-impact team that does the same.