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.