Director, Analytics Engineering

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...