Data Engineer

About the role

David is a fast‑growing food brand building high‑protein, low‑calorie products. The Data Engineer will co‑own the company’s data infrastructure and create AI‑powered workflows that automate manual, repetitive tasks across the organization.

Key responsibilities

• Design, build and maintain ETL pipelines from source systems (NetSuite, Shopify, retail platforms/EDI) into BigQuery with automated testing, monitoring and alerting.
• Develop well‑documented dbt models covering sales, inventory, fulfillment, finance and the in‑house S&OP platform.
• Partner with Finance, Retail, Supply Chain and Growth teams to translate business requirements into data solutions and establish modeling, documentation and governance standards.
• Co‑own the semantic layer and BI tooling (Omni), defining metrics and curating models for reporting.
• Design and deploy AI‑powered workflows for document parsing, data extraction, classification and enrichment, including evaluation frameworks and human‑in‑the‑loop processes.
• Manage credentials, sensitive data and third‑party integrations with appropriate access controls.
• Build scripts, automations and lightweight internal tools to replace manual processes and support recurring reporting and ad‑hoc analyses.

Required profile

• 2+ years of professional experience in data engineering, analytics engineering or a closely related technical role.
• Strong SQL and data modeling expertise, with knowledge of dimensional modeling and incremental transformation patterns.
• Hands‑on experience with dbt and a cloud data warehouse (BigQuery).
• Proficiency in Python for building pipelines, automation and data workflows.
• Familiarity with modern AI tooling and ability to implement reliable AI‑driven outputs.

Required skills

• SQL
• Data modeling
• dbt
• BigQuery
• Python
• AI tooling