Data Engineer

David Protein; New York (NY); Presencial; USD 150.000 - 200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health, Vision, Dental Insurance (100%

Equity opportunity

401(k)

Gym expenses

Paid time off

Office in NYC, 5 days/week

Descripción de la vacante

David Protein in New York City is building a data platform to turn ERP, retail, e-commerce, finance, and supply chain data into reliable pipelines and trusted analytics. The Data Engineer will co-own the data infrastructure and design AI-powered workflows to automate manual tasks across the organization.

The role focuses on designing ETL pipelines into BigQuery, developing canonical dbt models, and collaborating with Finance, Retail, and Growth to set data standards and governance.

Formación

• 2+ years of professional experience in data engineering, analytics engineering, or a closely related technical role.
• Strong SQL and data modeling skills; able to design clean, well-documented models.
• Production experience with dbt and a cloud data warehouse.
• Proficiency in Python for pipelines, automation, and data workflows.
• Working fluency with modern AI tooling.
• Nice to have: TypeScript and full-stack experience (Next.js/React), Looker/BI modeling, ERP, supply chain, or CPG data.

Responsabilidades

• Co-own David's data infrastructure and build AI-powered workflows to automate manual work.
• Design, build, and maintain ETL pipelines from source systems into BigQuery with data quality testing.
• Develop canonical dbt models spanning sales, inventory, finances, and S&OP platforms.
• Partner with Finance, Retail, Supply Chain, and Growth to turn requirements into data solutions.
• Co-own semantic layer and BI tooling (Omni, Looker) and drive metrics definitions.
• Design and deploy AI-powered workflows for document parsing, data extraction, and enrichment.

Conocimientos

Data engineering

SQL & data modeling

Python

AI tooling

Herramientas

dbt

Cloud data warehouse

Looker

PostgreSQL

Next.js/React

ERP/CPG data

Descripción del empleo

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.

• 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.

• 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.