Data Engineer, AI & Analytics

Role Overview

As a Data Engineer on the Data Team, you’ll own the core data foundation for Power Digital, working end-to-end from raw ingestion to serving layers that support agency, client, internal, and AI consumers. You’ll design, build, and maintain the core data foundation, handling API changes, deprecated fields, and retroactive restatement of conversion data. You’ll also model across sources to reconcile spend, impressions, conversions, and revenue across multiple platforms.

What You Will Do

Your day-to-day responsibilities will include building ingestion that handles API changes and deprecated fields, modeling across sources to reconcile data, and contributing to client-bespoke modeling on top of the core layer. You’ll also use AI-agentic workflows to accelerate development and build intelligent data infrastructure.

Why It Might Be a Fit

You might be a fit if you’re a data engineer at a brand or retailer who wants to work closer to the decisions your data drives, or if you’ve built marketing pipelines at an agency or martech company and know how they break.

Requirements

• 3+ years in data or analytics engineering
• 1+ years owning a dbt project of meaningful size in production
• Advanced proficiency in Python and SQL
• Deep expertise in dbt
• Strong command of Snowflake and the surrounding cloud data stack
• Experience modeling in a multi-tenant environment
• Working knowledge of marketing and advertising datasets
• Proven experience designing and managing end-to-end data lifecycles
• Familiarity with cloud-native infrastructure (GCP) and infrastructure-as-code principles
• Real adoption of AI-agentic development workflows
• Demonstrated ability to architect AI-ready data models
• Experience with Git and CI/CD best practices

Benefits

• Competitive salary
• Equity
• Health insurance
• Paid time off
• Retirement plan
• Learning budget
• Parental leave
• Wellness programs
• Visa/relocation assistance
• Remote flexibility
• Stipends
• Bonus/commission
• Paid holidays