Director, Analytics Engineering

Tebra only initiates contact with candidates via email from an official Tebra email address (@, @, or @) or through our applicant tracking system, Greenhouse. We will only ask you to provide sensitive personal information through our official application portal — not via social media or text message. We do not conduct interviews via instant messaging.

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.

- Evaluate and adopt tooling and best practices as the business data ecosystem evolves.

Your Professional Qualifications

- 7+ years of experience in data, with 3+ years in analytics engineering or a closely adjacent function.

- 5+ years of people management experience; you've built and developed teams, not just led them.

- Deep, hands-on expertise with dbt — you've built production-grade dbt projects and can speak fluently to modeling patterns, testing, macros, and CI/CD.

- Strong Snowflake proficiency and ecosystem —