Director, Analytics Engineering

About the Role

We're looking for a Director of Business Analytics Engineering to lead and grow the data modeling function within our Business Data & Analytics organization — a player/coach who thrives at the intersection of technical depth and people leadership. You'll own the data models, transformation layer, and semantic foundation that power business decision-making, while building and mentoring a high-performing team of analytics engineers.

This role sits at the core of how our internal business stakeholders — including Finance and the Data Analysts who support them — trust and use data. You'll partner closely with Finance-aligned Data Analysts to understand their analytical needs and translate those into clean, well-governed, reusable data assets. Our BI Engineering team owns the data ingestion pipelines and stack administration; your lane is the semantic layer and data models built on top of that foundation.

Your Area of Focus

• Technical Leadership:
  • Design and own a scalable, well-documented semantic layer that serves as the authoritative source of truth for business metrics and KPIs – the foundation Finance and Data Analysts rely on daily.
  • Establish data engineering best practices, modeling standards, and data quality controls across the organization.
  • Own and evolve our dbt + Snowflake transformation layer, including modeling standards, testing frameworks, documentation practices, and CI/CD workflows.
  • Drive data quality; build automated testing, alerting, and observability practices that give business stakeholders confidence in the numbers.
  • Partner with BI Engineering on the handoff between ingested data and modeled data, ensuring clean interfaces and clear ownership boundaries.
  • Ensure Tableau dashboards and Finance-facing self-service analytics are powered by clean, performant, well-modeled data assets.
• People Leadership:
  • Hire, develop, and retain a team of analytics engineers, setting clear expectations and career growth paths.
  • Foster a culture of craft — high standards for code quality, peer review, documentation, and knowledge sharing.
  • Partner with Finance leadership and their Data Analysts to deeply understand business data needs and translate them into the modeling roadmap.
  • Serve as a technical escalation point and hands-on contributor when the work demands it.
• Strategy & Stakeholder Engagement:
  • Serve as the primary data modeling and engineering partner to Finance and other internal business functions — translating analytical requirements into durable, reusable models that analysts can self-serve against.
  • Assist in establishing company-wide standards for metric definitions, data governance, documentation, and data stewardship across business functions.
  • Define the Business Analytics Engineering roadmap and communicate priorities and progress to senior leadership.
  • Champion data governance, lineage, and trust — ensuring business stakeholders always know which numbers to trust and why.
  • Collaborate on shared standards while maintaining clear ownership of the modeling and semantic layer domain.