Senior Data Platform Manager

Who you are

• A hands-on technical leader who focuses on scaling through team capability, prioritizing architectural depth over individual keyboard output
• A systems thinker who prioritizes fixing the class of problem over the instance, building durable solutions that solve recurring challenges
• A strategic partner to cross-functional pods, capable of translating complex business needs into concrete technical roadmaps for stakeholders
• A "Bridge-Builder" who moves seamlessly between architecting with senior engineers and explaining the organizational impact of data performance to leadership
• Pragmatic regarding technical debt, balancing delivery speed with the architectural discipline required to maintain a performant, stable platform
• Expertly opinionated about dimensional modeling and semantic layers, ensuring the platform footprint scales without creating fragmented definitions
• Clear-eyed about the steward’s responsibility when architecting controls for PHI and sensitive clinical datasets
• 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

What the job involves

• We are seeking a Director of Data Platform to take end-to-end ownership of our data lifecycle: from the moment information lands in our warehouse to its final modeling and delivery to the stakeholders and systems driving our mission forward
• In this role, you will architect the platform’s reliability and performance, managing pipeline orchestration, our dbt project, and the foundational models that keep BI, experimentation, and AI tools synchronized
• You will navigate a complex domain involving medical claims, clinical outcomes, and multi-payer eligibility for 2.2 million members, all within a strict HIPAA-compliant environment. To achieve this, you will lead and mentor a senior, distributed data engineering team comprising both domestic and offshore talent
• You will serve as a strategic peer to the Analytics & Data Science team
• Together, you will define the architectural vision for our data foundation, ensuring a seamless handoff where they build downstream analytics on the standards you establish
• Success in this role requires maintaining a clear, documented boundary between core platform systems and analytics engineering to eliminate ambiguity in ownership
• As a hands-on technical leader, you will focus on scaling the platform through your team’s capabilities rather than individual output
• You are a systems thinker who prioritizes fixing the class of problem over the instance, creating durable capabilities that accelerate every downstream team
• You will drive excellence through rigorous design reviews and architectural discipline
• Your impact will span the entire organization, partnering with Analytics, Finance, and cross-functional pods dedicated to clinical and member-facing challenges
• You will make these collaborations effective by conducting standing roadmap reviews and ensuring platform capacity is allocated transparently and strategically, rather than responding to one-off, isolated requests
• ARCHITECT THE DATA FOUNDATION:
• 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
• EMPOWER AND SCALE THE TEAM:
• 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
• PARTNER STRATEGICALLY ACROSS THE BUSINESS:
• 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
• STEWARD CRITICAL DATA OPERATIONS:
• 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
• LEAD AI-NATIVE ENGINEERING:
• 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
• Signals of Success:
• Cross-functional teams in Product and Finance accelerate their velocity because the underlying data foundation is accurate, stable, and self-service
• Ambiguity regarding metric accuracy is eliminated through a unified context layer that synchronizes definitions across BI, experimentation, and AI platforms
• Platform priorities and roadmaps are communicated transparently, ensuring every stakeholder understands the strategic rationale behind capacity allocation
• Vital business reporting and financial pipelines operate with high resilience, free from single points of failure or reactive troubleshooting
• Your engineering team achieves greater technical depth and autonomy under your mentorship and leadership

Benefits

• Unlimited PTO
• Flexible working hours
• Flexible working location
• Paid health insurance
• 401k, bonus & stock options