David Protein

Direct-to-consumer protein supplements for athletes

Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-timeNew York, NY, USA$150k - $200k /yr

About the Job

Requirements

At least 2 years of professional experience in data engineering, analytics engineering, or a closely related technical role.
Strong SQL and data modeling skills, including the ability to design clean, well-documented models from messy operational and ERP data, and understanding of dimensional modeling and incremental transformation patterns.
Production experience with dbt and a cloud data warehouse.
Proficiency in Python for pipelines, automation, and data workflows, including writing clean, testable code with proper version control.
Working fluency with modern AI tooling.
A track record of building pipelines, systems, or automations that others depend on, gained in a professional setting, side project, or open-source contribution.
Ability to operate independently while clearly communicating priorities and initiatives to the team.
Desire to build an early-stage CPG company with a mission to help people increase muscle and decrease fat.

Responsibilities

Co-own the company's data infrastructure and build AI-powered workflows that eliminate manual, repetitive work across the organization.
Design, build, and maintain ETL pipelines from source systems such as NetSuite, Shopify, and retail platforms/EDI into BigQuery, with automated testing, monitoring, and data-quality alerting.
Develop canonical, well-documented dbt models spanning sales, inventory, fulfillment, financials, and the in-house S&OP platform as the 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 the semantic layer and BI tooling (Omni), including model curation, metric definitions, and reporting used by leadership.
Design and deploy AI-powered workflows for document parsing, data extraction, classification, and enrichment in 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 to replace manual processes, working alongside engineers who own application development.
Automate recurring reporting and ad hoc analyses to support organizational visibility into key metrics.

Desired Qualifications

TypeScript and full-stack experience, including Next.js/React and Postgres.
Experience with agent frameworks and orchestration.
Semantic layer or BI modeling experience, such as Omni or Looker.
Experience with ERP, supply chain, or CPG data.

Data Engineer

David Protein · New York, United States · — · Posted 2026-11-02

Workplace: on_site

Department: Finance

Description

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.

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About the Company

David Protein

Direct-to-consumer protein supplements for athletes

David Protein creates and sells protein supplements to help athletes and fitness enthusiasts improve health and performance. Its products include protein powders, bars, and other nutritional supplements offered through its e-commerce platform and through partnerships with fitness centers and health stores. The system works by consumers purchasing directly online or via partner locations; products are formulated to support training and recovery with scientifically designed ingredients. The company differentiates itself through a focus on privacy and secure transactions for customer data, aiming to earn trust and protect personal information in the health market. Its goal is to grow a direct-to-consumer brand with reliable, science-based nutrition products that support athletic performance and overall well-being.

Company size: 201-500
Company stage: Series B
Total funding: $335M
Headquarters: New York City, New York
Founded: 2023

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