Director leading Homebase’s data engineering, data science, and applied AI teams. Building trusted data infrastructure and AI-powered tools for 150,000+ small businesses.
Responsibilities
Own and execute the Data & AI technical roadmap across data engineering, data platform, data science, and applied AI.
Lead and grow a 20+ person organization across four sub-teams, including managing managers and senior individual contributors.
Recruit, develop, and retain talent while building a culture of velocity, ownership, and craft excellence.
Own the reliability, scalability, and governance of Homebase’s data stack.
Partner with Product and Engineering to ship AI-powered product features, including LLM-based assistants, recommendation systems, and intelligent automation.
Own the MLOps lifecycle from experimentation through production.
Build experimentation frameworks, guardrail metrics, and evaluation pipelines.
Ensure models are reliable, fair, and cost-effective.
Coach leaders and drive organization-wide adoption of AI tools, workflows, and AI-assisted development practices.
Define standards for data quality, model monitoring, data contracts, and responsible AI use.
Serve as the authority on data architecture and AI governance.
Partner with Product, Growth, GTM, Finance, and CX to address data and AI needs.
Requirements
10+ years in data and/or AI/ML.
At least 5 years leading teams of 8+ across data engineering, data science, or applied AI.
Director-level leadership experience managing managers, building organizations, and driving technical strategy at scale.
Deep technical fluency across warehousing, orchestration, transformation, BI, production ML systems, LLMs, and experimentation platforms.
Strong product instincts connecting data and AI work to customer outcomes and business metrics.
Active use of AI to improve workflows and experience leading teams that ship AI-powered products.
Current knowledge of LLMs, agentic systems, and multimodal AI.
Ability to translate complex technical concepts for non-technical stakeholders.
Experience with modern data platforms such as Databricks, Snowflake, or similar.
Familiarity with Unity Catalog, Airflow, dbt, and ML platforms such as MLflow or Baseten is a strong plus.
Based in or willing to relocate to the Toronto area.
Willingness to collaborate in person Tuesdays and Wednesdays at the Toronto hub.
Bonus: experience building data and AI organizations at a SaaS or marketplace company serving SMBs.
Bonus: background establishing data-as-a-product disciplines, including data contracts, semantic layers, or data mesh concepts.
Bonus: experience with experimentation platforms and causal inference at scale.
Benefits
Stock options
TFSA/RRSP with 4% company match
Comprehensive medical, dental, and vision for you and your dependents
Flexible PTO
Company holidays
Designated focus periods
Access to paid AI tools with minimal restrictions
Maternity/Parental Leave EI top-up support offered after 6 months of service
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