Director, Analytics Engineering

About this role

Tebra only initiates contact with candidates via email from an official Tebra email address (@tebra.com, @patientpop.com, or @kareo.com) 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 — query optimization, warehousing strategy, cost management.

• Experience partnering with Finance, FP&A, or business operations teams — you understand the domain and can speak their language as fluently as SQL.

• Fluency with Tableau or comparable BI tools; you understand what good data modeling looks like from the consumer's perspective.

• Track record of building and maintaining semantic/metrics layers and defining organizational standards for KPIs.

• Strong communication skills — equally comfortable in a dbt PR review and a presentation to the VP of…