FacilityOS
Senior Data Engineer
Toronto · Senior
Sponsorship not specifiedDetected 5 days ago
Data StructuresBigQuerySnowflakeVector DatabasesOAuthAirflowdbtData EngineeringRAGAgentic AIAI OrchestrationCybersecurityComplianceMicrosoft Office
About the role
- The Data Engineer reports to the VP of Engineering and owns the data infrastructure that powers FacilityOS's AI agents and broader analytics needs. This role is foundational to the company's AI strategy: agents are only as good as the data they can reliably access, and the Data Engineer is responsible for building and maintaining that foundation.
- FacilityOS's data foundation exists today but requires expansion to support the next phase of AI-driven growth. The Data Engineer drives that expansion, schema design, pipeline quality, and data governance, working in close partnership with the AI Engineer, who builds the agents that orchestrate against this data.
- The Data Engineer reports to the VP of Engineering and owns the data infrastructure that powers FacilityOS's AI agents and broader analytics needs.
Responsibilities
- Own the design, build-out, and ongoing maintenance of FacilityOS's data warehouse and data lake
- Design and evolve schemas that support both AI agent orchestration and broader business analytics
- Build and maintain reliable, well-monitored data pipelines across source systems
- Partner with VP Infosec to ensure data handling meets ISO27001 and SOC2 Type 2 compliance requirements
- Build agents to meet FacilityOS's ISO27001 and SOC2 Type 2 compliance requirements from the ground up
- Partner with the AI Engineer to ensure agents have reliable, structured, and current data to work against
- Support department managers by making departmental data accessible and AI-ready for their agent initiatives
Requirements
- 5+ years of experience in data engineering, including schema design, ETL/ELT pipeline development, and data warehouse/lake architecture
- Hands-on experience with Fabric or alternative modern data stack tools (e.g., dbt, Airflow, Snowflake, BigQuery, or equivalent)
- Working knowledge of data governance, quality, and security practices in an enterprise environment
- Familiarity with the data requirements of AI/RAG systems (structured retrieval, embeddings, vector stores) is a strong asset
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
Nice to have
- Familiarity with compliance frameworks such as SOC2 or ISO27001 is a plus
- Experience in a SaaS or enterprise technology environment preferred
Compensation
- 🎉 Two annual parties in a year
Benefits
- Own the health and cost of the platform as usage grows
Company info
- Establish and enforce data governance standards, including data quality checks, lineage tracking, and access controls
- Ensure data structures meet the AI-readiness standards required for agent orchestration
- Act as a technical resource within the AI Tech/Integration SWAT for data-related blockers
- Connect agents into the core business systems departments already work in
- Microsoft 365, Outlook/email, and Teams, so agents can read, draft, notify, and act within existing workflows rather than requiring new interfaces
- Build and maintain secure authentication and permissioning patterns (e.g., Microsoft Graph API, OAuth) for agents acting inside business systems on a user or department's behalf
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This listing is sourced directly from FacilityOS's careers page and normalized into a canonical job model.