Tebra provides an integrated EHR+ platform that streamlines clinical, billing, telehealth, and marketing workflows for private healthcare practices.
<div class="content-intro"><p>Tebra only initiates contact with candidates via email from an official Tebra email address (@<a class="c-link" href="http://tebra.com/" target="_blank" data-stringify-link="http://tebra.com" data-sk="tooltip_parent">tebra.com</a>, @<a class="c-link" href="http://patientpop.com/" target="_blank" data-stringify-link="http://patientpop.com" data-sk="tooltip_parent">patientpop.com</a>, or @<a class="c-link" href="http://kareo.com/" target="_blank" data-stringify-link="http://kareo.com" data-sk="tooltip_parent">kareo.com</a>) 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.</p></div><h1>About the Role</h1> <p>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.</p> <p>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.</p> <h1>Your Area of Focus</h1> <ul> <li>Technical Leadership:</li> <ul> <li>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.</li> <li>Establish data engineering best practices, modeling standards, and data quality controls across the organization.</li> <li>Own and evolve our dbt + Snowflake transformation layer, including modeling standards, testing frameworks, documentation practices, and CI/CD workflows.</li> <li>Drive data quality; build automated testing, alerting, and observability practices that give business stakeholders confidence in the numbers.</li> <li>Partner with BI Engineering on the handoff between ingested data and modeled data, ensuring clean interfaces and clear ownership boundaries.</li> <li>Ensure Tableau dashboards and Finance-facing self-service analytics are powered by clean, performant, well-modeled data assets.</li> </ul> <li>People Leadership:</li> <ul> <li>Hire, develop, and retain a team of analytics engineers, setting clear expectations and career growth paths.</li> <li>Foster a culture of craft — high standards for code quality, peer review, documentation, and knowledge sharing.</li> <li>Partner with Finance leadership and their Data Analysts to deeply understand business data needs and translate them into the modeling roadmap.</li> <li>Serve as a technical escalation point and hands-on contributor when the work demands it.</li> </ul> <li>Strategy & Stakeholder Engagement:</li> <ul> <li>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.</li> <li>Assist in establishing company-wide standards for metric definitions, data governance, documentation, and data stewardship across business functions.</li> <li>Define the Business Analytics Engineering roadmap and communicate priorities and progress to senior leadership.</li> <li>Champion data governance, lineage, and trust — ensuring business stakeholders always know which numbers to trust and why.</li> <li>Collaborate on shared standards while maintaining clear ownership of the modeling and semantic layer domain.</li> <li>Evaluate and adopt tooling and best practices as the business data ecosystem evolves.</li> </ul> </ul> <h1>Your Professional Qualifications</h1> <ul> <li>7+ years of experience in data, with 3+ years in analytics engineering or a closely adjacent function.</li> <li>5+ years of people management experience; you've built and developed teams, not just led them.</li> <li>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.</li> <li>Strong Snowflake proficiency and ecosystem — query optimization, warehousing strategy, cost management.</li> <li>Experience partnering with Finance, FP&A, or business operations teams — you understand the domain and can speak their language as fluently as SQL.</li> <li>Fluency with Tableau or comparable BI tools; you understand what good data modeling looks like from the consumer's perspective.</li> <li>Track record of building and maintaining semantic/metrics layers and defining organizational standards for KPIs.</li> <li>Strong communication skills — equally comfortable in a dbt PR review and a presentation to the VP of Finance.</li> </ul> <h1>Preferred Qualifications</h1> <ul> <li>Familiarity with or experience in SaaS business models and related metrics.</li> <li>Experience with data observability tooling (Monte Carlo, Elementary, etc.).</li> <li>Familiarity with data mesh, data products, or federated ownership models.</li> <li>Exposure to ML feature engineering or working alongside Data Science teams.</li> <li>Background in a high-growth or scaling analytics environment.</li> </ul> <p><strong>#LI-BG1 #LI-Remote</strong></p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p>In compliance with California's pay transparency laws, the compensation range for this position will be provided a