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Salary: CAD 176,000 - 235,000 / annual
BuildOps is a commercial contracting platform that has recently achieved unicorn status ($1B valuation) with $127M in Series C funding. Data is central to the company's AI-first strategy, and this role leads the unified Data & AI engineering function.
As Director of Engineering, Data, you will report to the VP of Engineering and own BuildOps' data platform and architecture end-to-end. Your responsibilities include:
• Own the complete data platform including ingestion, transformation, orchestration, ML, and streaming strategy that scales efficiently with the business
• Build scalable customer and partner data onboarding capabilities to bring data into BuildOps quickly and reliably, reducing time to first value
• Run data systems with production-grade discipline: monitoring, alerting, SLAs, incident response, lineage tracking, freshness guarantees, and clear ownership for critical datasets
• Create the data foundation for AI and ML products, with accurate, well-documented inputs and appropriate training, inference, and feature infrastructure as products mature
• Establish governance that enables speed: access controls, data classification, audit trails, PII handling, and practical data contracts that teams can depend on
• Hire, develop, and lead a strong data engineering team; establish operating rhythms for planning, on-call rotation, and stakeholder intake
• Help define BuildOps' data strategy over the next 3–5 years and shape how the company builds data-powered products
This is a foundational leadership role for someone who can think long-term about architecture while staying close to the work. You will influence across Product, Engineering, GTM, Finance, and the executive team, translating technical decisions into business impact and business goals into technical direction.
BuildOps operates hubs in Los Angeles, San Francisco, Toronto, and Raleigh with hybrid work schedules. The company is backed by investors including Meritech Capital, BOND, SE Ventures, and Schneider Electric, with advisors including former Twitter CEO Dick Costolo and former Salesforce President Gavin Patterson.
REQUIREMENTS:
• 10+ years in data or software engineering, including experience building and scaling teams of 10+ engineers, with a track record of hiring well, growing leaders, and leading through managers as well as individual contributors
• Deep hands-on experience with modern data platforms: cloud warehouse or lakehouse (Snowflake or Databricks), dbt and ELT patterns, orchestration tools (Airflow), streaming technologies (Kafka or Kinesis); AWS experience strongly preferred
• Direct experience building data systems that support production ML use cases (not just analytics), including understanding of feature stores, training data, real-time inference, and build-vs-buy tradeoffs for ML platform capabilities
• Track record of operational excellence in data: monitoring, SLAs, incident response, and data quality practices applied with the same rigor as customer-facing systems
• Experience delivering customer-facing data products (reporting, analytics, APIs) in B2B SaaS environments where performance, reliability, and trust matter
• Strong architectural judgment: knowing when to build vs. buy, designing for change, and sequencing investments behind validated needs rather than overbuilding
• Pragmatic approach to governance with security and compliance built in, documentation and contracts that stay current, and access models balancing control with self-service
• Early-stage or scale-up experience in Series B–D companies is a plus; vertical SaaS or construction tech experience is helpful but not required
You are a builder comfortable with ambiguity and greenfield work, able to move quickly and ship an MVP while making sound long-term decisions. You are both hands-on and strategic—willing to write code, debug issues, and carry operational responsibility while maintaining a clear multi-year vision.
