Data Engineer - AI Pipelines for Fast-Growth CPG (Equity)

Medici Brands; New York (NY); On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

Health, Vision, Dental Insurance

401(k)

Equity

Gym expenses

PTO

Job summary

David is seeking a Data Engineer to co-own data infrastructure and build AI-powered workflows that automate manual tasks across the organization. You will turn ERP, retail, e-commerce, and finance data into reliable pipelines and trusted data models to enable cross-functional analytics.

In this role, you will design ETL pipelines into BigQuery, develop dbt models, and collaborate with Finance, Retail, and Supply Chain to standardize data governance.

Qualifications

• 2+ years of professional experience in data engineering, analytics engineering, or a closely related technical role.
• Strong SQL and data modeling skills with dimensional modeling knowledge.
• Production experience with dbt and a cloud data warehouse.
• Proficiency in Python for pipelines, automation, and data workflows.
• Working fluency with modern AI tooling.

Responsibilities

• Design, build, and maintain ETL pipelines from source systems into BigQuery with automated testing and data quality monitoring.
• Develop canonical, well-documented dbt models for sales, inventory, financials, and planning data.
• Partner with Finance, Retail, Supply Chain, and Growth to turn business requirements into data solutions.
• Co-own semantic layer and BI tooling (Omni) model curation and metric definitions for reporting.
• Design and deploy AI-powered workflows for data extraction, classification, and enrichment.

Skills

SQL

Data modeling

Python

AI tooling

Tools

dbt

BigQuery

Looker

Job description

David is seeking a Data Engineer to co-own data infrastructure and build AI-powered workflows that automate manual tasks across the organization. You will turn ERP, retail, e-commerce, and finance data into reliable pipelines and trusted data models to enable cross-functional analytics.

In this role, you will design ETL pipelines into BigQuery, develop dbt models, and collaborate with Finance, Retail, and Supply Chain to standardize data governance.