Director, Data Platform

• Take end-to-end ownership of the data lifecycle, managing everything from pipeline orchestration and our dbt project to the warehouse infrastructure, ensuring peak performance and reliability.
• Instill a 'Data-as-a-Product' philosophy across the organization, treating internal teams as customers by defining rigorous SLAs for data quality, freshness, and accessibility.
• Establish proactive data observability and contracts, shifting the culture from reactive troubleshooting to a disciplined system that identifies regressions before they impact downstream stakeholders.
• Translate ambiguous business needs into concrete technical roadmaps, leading discovery with cross-functional partners to turn recurring pain points into scalable architectural solutions.
• Direct the evolution of our foundational models, applying expert-level dimensional modeling and star schema designs to ensure the platform scales with our AI and analytics footprint.
• Serve as a strategic partner to Analytics & Data Science, co-architecting the semantic and context layers to establish the standards they build upon.
• Maintain a documented, transparent boundary between our core product systems and the analytics environment to ensure clarity of ownership.
• Mentor and scale a high-performing, distributed data engineering team comprising domestic and offshore talent.
• Delegate with strategic intent, focusing on expanding platform capacity through the team's technical growth rather than your own individual keyboard output.
• Drive technical excellence and architectural discipline through rigorous design reviews, RFCs, and code audits.
• Act as the technical counterpart to the Analytics & Data Science leadership, ensuring platform investments align with the company's long-term trajectory.
• Conduct standing roadmap reviews with key stakeholders to prioritize effectively, unblock initiatives, and ensure capacity allocation is transparent.
• Collaborate with cross-functional pods to ensure data requirements are integrated into the problem definition phase, creating durable rather than isolated solutions.
• Prioritize fixing classes of problems over instances, building permanent platform capabilities that solve recurring stakeholder challenges.
• Direct the data infrastructure supporting revenue cycle management and billing, ensuring the pipelines powering Finance remain flawless.
• Manage the integrations and models for our member lifecycle systems, guaranteeing that engagement and attribution data remain consistent across the warehouse.
• Build resilience into vital business reporting through sophisticated automation, comprehensive documentation, and a culture of shared accountability.
• Lead the platform's HIPAA compliance efforts, architecting the controls for PHI access, deidentification, and audit readiness in partnership with Security.
• Foster an AI-first engineering culture where tools like Claude Code serve as genuine force multipliers for refactoring and documenting infrastructure.
• Establish the governance standards and safety guardrails required for the responsible application of AI within our engineering workflows.
• Design the underlying context layer for our AI-powered analytics tools, ensuring generated insights are accurate and dependable by construction.

• Over a decade of expertise in data engineering or platform domains, with at least 4 years dedicated to leading and scaling high-performing teams.
• Demonstrated hands-on mastery of modern cloud data warehouses (Snowflake, BigQuery, or Redshift) and sophisticated orchestration frameworks like Dagster or Airflow.
• Expert-level dbt proficiency, encompassing large-scale project architecture, semantic layer implementation, and seamless integration with BI tools such as Looker or Omni.
• Advanced command of dimensional modeling at scale, supported by expert SQL abilities and strong Python engineering skills.
• A deep commitment to Data Reliability Engineering (DRE), with a proven history of architecting CI/CD pipelines and automated quality testing within dbt ecosystems.
• The ability to influence without authority, successfully driving the adoption of architectural standards and new tooling across cross-functional engineering pods.
• Experience serving as a strategic technical peer to Analytics and Data Science teams, functioning as an architectural partner rather than a support service.
• A successful background in managing distributed engineering talent, including domestic and offshore collaborators.
• Professional fluency in HIPAA regulations and experience architecting infrastructure for sensitive healthcare data, including claims, eligibility, and clinical records.
• Operational experience with AI-native development tools like Cursor or Claude Code, utilizing them as force multipliers in production workflows.

Pay range: $200K - $225K

• Remote-First Culture — Work from anywhere with a flexible schedule.
• Unlimited PTO — We prioritize rest and recharging.
• Comprehensive Healthcare — Robust medical, dental, and vision coverage.
• Financial Wellness — 401k, performance bonuses, and equity options.
• Personalized Nutrition — Access to our network of Registered Dietitians.