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.

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