Director, Data Engineering

SQUIRE•Ontario, ON

1d•$200,000 - $230,000•Remote

About The Position

At SQUIRE, trusted data turns information into action - powering everything from company-wide reporting and automation to the AI capabilities shaping our next chapter. We're hiring a Director, Data Engineering to build and lead our Data organization through a player-coach model, spending approximately half your time hands-on in the code and the other half developing engineers, setting technical direction, and owning the organization’s strategy. You’ll own SQUIRE’s long-term data architecture and lead a growing team spanning Data Engineering, Machine Learning Engineering, and Analytics. Success in this role means building a data foundation the company trusts by default, with reliable pipelines, clear standards, and scalable systems. You'll have the authority and accountability to make architectural and organizational decisions needed to move the function forward while helping the team grow in both capability and impact. As SQUIRE continues to scale, your work will directly enable more confident decision-making, stronger automation, and AI use cases that power our next phase of growth.

Requirements

8+ years in data or software engineering, including 4+ years managing engineers
Experience building and leading a multidisciplinary data organization (data, ML, analytics, software) of 5+ people
Advanced SQL and Python skills, along with strong MDM fundamentals, with the technical depth to lead by example
Hands-on experience with Snowflake (or equivalent), dbt, and an orchestration tool such as Airflow, Dagster, or Prefect, beyond just an architectural understanding
Direct experience setting AI and LLM enablement strategy and building with LLM tooling
Comfortable operating at Director scope (owning budgets, advocating for roadmaps, and translating technical tradeoffs for non-technical stakeholders) while remaining directly involved in technical execution

Nice To Haves

Experience building AI agents with LLMs (wired models into real systems with tool use, retrieval, and orchestration) and with the ability to guide others doing similar work
Backend engineering experience (ideally in JS/TS) with sufficient depth to effectively evaluate architecture
Strong ML and MLOps knowledge, with the ability to set direction, assess technical tradeoffs, and support ML Engineering Leads
Experience with Salesforce, Stripe, Gong, or reverse ETL (Polytomic), and data governance / PII handling at a company-wide policy level

Responsibilities

Design, build, and debug the highest-impact pipelines, connecting our business systems, including CRM, billing, and internal platforms to our Snowflake warehouse, in both directions
Own the data strategy and architecture across a multi-year horizon, while maintaining deep, hands-on familiarity with the systems and their edge cases
Establish technical direction and standards for pipeline design, data modeling, and data quality across the org; personally build and ship the highest-risk or most ambiguous work
Build, structure, and lead a growing Data organization of 5+ across Data Engineering, ML Engineering, and Analytics
Own headcount planning, hiring strategy, and budget for the Data organization
Partner with the Chief Product and Technology Officer and cross-functional leaders to translate company strategy into data contracts and platform investments
Lead audits of existing integrations and automations, and determine what should be replaced and how that work should be prioritized
Champion AI and automation enablement company-wide, ensuring agents and LLM use cases are built on a trusted data foundation, while remaining hands-on in building select enablement capabilities