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
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
Don’t let this list stop you from applying - If you are interested in the role, we’d love to hear from you!
🚀 WHY SQUIRE?
As a Director, Data Engineering, you’ll have real ownership over a function the whole company depends on, a mandate to develop its leadership structure, and the charter to define the data foundation for SQUIRE's AI future — with the authority to turn that strategy into a lasting practice