Data Engineer

*Company:* David creates tools to increase muscle and decrease fat. Our first product is a protein bar. More broadly, David is a platform to develop high-protein, low-calorie, blood-sugar-friendly foods that are craveable. This is a compelling opportunity to join an exciting new food brand as we enter a critical growth stage. David is led by CEO Peter Rahal, the Cofounder and Former CEO of RXBAR ($600M exit to Kellogg in 2017). We have strong aspirations to become the most popular high-protein bar in North America and beyond. *Roles & Responsibilities:* The Data Engineer will co-own David's data infrastructure and build AI-powered workflows that eliminate manual, repetitive work across the organization. This role sits at the center of how the company turns operational data from our ERP, retail platforms, e-commerce channels, finance platforms, and supply chain systems into reliable pipelines, trusted data models, and automated workflows that are leveraged cross-functionally. *Data pipelines & modeling* * Design, build, and maintain ETL pipelines from source systems (NetSuite, Shopify, retail platforms/EDI, etc) into BigQuery, with automated testing, monitoring, and alerting for data quality. * Develop canonical, well-documented dbt models for spanning sales, inventory, fulfillment, financials, and our in-house S&OP platform that serve as the trusted foundation for reporting and analytics. * Partner with Finance, Retail, Supply Chain, and Growth to turn business requirements into data solutions, and help set standards for modeling, documentation, and governance. * Co-own our semantic layer and BI tooling (Omni): model curation, metric definitions, and the reporting leadership relies on. *Internal tooling & automation* * Design and deploy AI-powered workflows for document parsing, data extraction, classification, and enrichment as part of data pipelines and operational processes. * Implement evaluation frameworks and human-in-the-loop patterns to ensure reliability and accuracy of AI-driven outputs. * Manage credentials, sensitive data, and third-party integrations, and design workflows with appropriate access controls and guardrails. * Build scripts, automations, and lightweight internal tools that replace manual processes, working alongside engineers who own application development. * Automate recurring reporting and ad hoc analyses to support organizational visibility to key metrics. *Requirements* * 2+ years of professional experience in data engineering, analytics engineering, or a closely related technical role. * Technical proficiency: * Strong SQL and data modeling skills: you can design clean, well-documented models from messy operational and ERP data, and you understand dimensional modeling and incremental transformation patterns. * Production experience with dbt and a cloud data warehouse. * Proficiency in Python for pipelines, automation, and data workflows: clean, testable code with proper version control. * Working fluency with modern AI tooling. * Nice to have: TypeScript and full-stack experience (Next.js/React, Postgres), agent frameworks and orchestration, semantic layer / BI modeling (Omni, Looker), and experience with ERP, supply chain, or CPG data. * A track record of building pipelines, systems, or automations that other people actually depend on in a professional setting, a side project, or an open-source contribution. * The ability to operate independently while clearly communicating priorities and initiatives to the rest of the team. * Humble, self-aware, and curious. * A desire to build an early stage CPG company with a mission to help people increase muscle and decrease fat. *Benefits* * This is a full-time role. * Salary: $150K - $200K per year, inclusive of cash bonus based on attainment of company targets * Company equity opportunity * 100% covered Health, Vision, Dental Insurance * 401(k) * Additional perks, such as covered gym expenses * Substantial and required PTO * We work in the office 5 days per week in New York City – when culture lines up, it is fun to be in the office together.