- Location
- New York, New York, United States · published
- Department
- Marketing
- Source
- Workable
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.