Workforce Intelligence Engineer

About the role

Crusoe's People Science & Workforce Intelligence team builds the systems, models, and tooling that power how the company understands and acts on its workforce. This role is the technical engine enabling that work — and an opportunity to grow into full ownership of it.

Responsibilities

• Contribute to and take growing ownership of our data engineering stack: dbt models in BigQuery, staging layers from sources like Rippling, Ashby, and Visier, and event-grain models that capture workforce changes with the fidelity HR analytics requires.
• Design and deploy agentic systems that automate high-friction HR workflows and surface actionable workforce intelligence — from intelligent classification and matching to multi-step agents that interact with HR platforms.
• Serve as the technical liaison between People Science and Crusoe's central IT organization for work that extends beyond our data stack. Triage the technical backlog, determine what gets built in-house versus scoped through IT versus solved with a vendor, and drive delivery once the call is made.
• Build custom internal tooling where commercial HR products fall short — from rapid prototypes that validate a direction quickly to production-quality tools that replace vendor contracts.
• Build the pipelines and data products that surface workforce intelligence to leadership — headcount, attrition, performance distributions, compensation equity signals, org health metrics. Translate complex, multi-source analyses into clear narratives that drive decisions at the executive level.

Requirements

• Foundational HR domain expertise: You've worked in or alongside HR systems — HRIS, ATS, compensation or performance platforms — and you understand how HR processes translate into data.
• Data engineering fundamentals with room to grow: You have hands-on experience writing production SQL, working with dbt or a similar transformation framework, and thinking about data modeling — grain, lineage, schema design.
• Working software engineering ability: You've written code that runs in production - pipelines, API integrations, scheduled jobs, or lightweight applications.
• Exposure to AI/agent development: You've experimented with or built LLM-powered tools — even if you haven't yet shipped a production agent.
• AI-assisted development as a working style: You use tools like Cursor, Claude Code, or equivalent to move faster than traditional engineering timelines — building functional prototypes rapidly, iterating in the open, and scaling your own output beyond what solo engineering typically allows.
• Data storytelling and communication: You can translate a technical analysis into something a non-technical stakeholder can act on.

Qualifications

• Curiosity and coachability: You take ownership of your work, seek feedback actively, and apply it quickly.
• Self-directed execution: You navigate ambiguity, form a point of view, build something, and learn from it.

Skills

• Foundational HR domain expertise
• Data engineering fundamentals
• Working software engineering ability
• Exposure to AI/agent development
• AI-assisted development as a working style
• Data storytelling and communication

Benefits

• Competitive compensation and equity packages
• Restricted Stock Units
• Paid time off, paid holidays & leave of absence programs
• Comprehensive health, dental & vision insurance
• Employer contributions to HSA account
• Paid parental leave
• Paid life insurance, short-term and long-term disability
• Mental health & wellness support
• Commuter benefits (parking & transit)
• Cell phone stipend
• 401(k) Retirement plan with company match up to 4%
• Volunteer time off
• Global travel insurance & emergency assistance
• Daily meals allowance
• Additional perks & programs specific to location