Director, Data Platform

Job description

**ABOUT US** Foodsmart is the leading telenutrition and foodcare solution, backed by a robust network of Registered Dietitians. Our platform is designed to foster healthier food choices, drive lasting behavior change, and deliver long-term health outcomes. Through our highly personalized, digital platform, we guide our 2.2 million members—including those in employer-sponsored health plans, regional and national Medicaid managed care organizations, Medicare Advantage plans, and commercial insurers—on a tailored journey to eating well while saving time and money. Foodsmart seamlessly integrates dietary assessments and nutrition counseling with online food ordering and cost-effective meal planning for the entire family. We partner with national and regional retailers across the U.S., many of whom accept SNAP/EBT, making healthier food more accessible. In 2024, Foodsmart secured a $200 million investment from TPG's Rise Fund to help expand our reach, particularly to low-income workers disproportionately affected by diet-related diseases. **Our core values:** 👥 Customer First — You start with the member and work backwards. 🚀 Make It Happen — You act with urgency, use data, and hold high standards. 🤝 One Team — You collaborate with respect and commit as a group. **ABOUT THE ROLE** Data is the lifeblood of Foodsmart. It empowers our executive leadership to steer the business, enables clinical teams to validate member health outcomes, and ensures our health plan partners can hold us to the highest standards. Because our AI-driven insights are only as dependable as the infrastructure supporting them, we require a dedicated architect to lead this foundational work. 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. ### You will **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. ### 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. ### You have - 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. ### 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.