What You'll Do

Data Foundations

• Build and own dbt models end-to-end — from raw source ingestion through to staging, intermediate, and reporting layers — for the PWI domain, covering HRIS, headcount, absence, attendance, and adjacent people data sources.
• Design and maintain scalable warehouse schemas in Snowflake, with clear data lineage, documentation, and version-controlled code (Git).
• Define, document, and steward metric definitions and the semantic layer for people data, ensuring reliable KPI logic and metric consistency across the domain.
• Implement data quality testing, monitoring, and alerting so that data issues are caught early and fixed proactively — not discovered by stakeholders.

Analytical Delivery

• Deliver structured analysis on headcount, attrition, absence and attendance, org design, manager effectiveness, and compensation for PBPs and PWI leadership — forming clear hypotheses and producing decision-ready outputs, not just data dumps.
• Build and maintain intuitive dashboards and reporting that allow stakeholders to self-serve on day-to-day questions without requiring analyst involvement.
• Support MBR and QBR cycles with data storytelling: own the narrative, not just the numbers.
• Partner with PBPs to diagnose root-cause data gaps, translate urgent business needs into analytical deliverables, and systematically improve the quality of people data over time.

Stakeholder Partnership

• Act as the embedded analytical partner for the PWI function — showing up proactively, anticipating needs, and flagging risks before they escalate.
• Present findings directly to People leadership with confident, prescriptive recommendations.
• Enable PBPs to work more independently with data through documentation, self-serve tools, and direct coaching.

What You Need to Succeed

Must-haves

• 5+ years in analytics engineering, analytics, or a hybrid of both — you have done both the building and the analysis, not just one side.
• Expert-level dbt: you have built models from raw source data, written tests, managed documentation, and understand lineage end-to-end — not just maintained existing models.
• Strong SQL: complex queries, performance optimization, ability to work across a Snowflake-based data warehouse without hand-holding.
• Analytical rigour: you structure ambiguous problems into hypotheses, identify the right metrics, and produce outputs that lead to decisions — not more questions.
• Clear communicator: you translate data into plain language for non-technical stakeholders, present confidently, and write documentation that people actually use.
• Experience with BI tooling (HEX, Tableau, Looker, or equivalent) for building stakeholder-facing dashboards and reporting.
• Comfortable with Git and version-controlled codebases as a daily practice.
• High ownership: you diagnose root causes, drive work independently, and don't wait to be told what matters next.
• Nice to have