Fuel Cycle

Senior Data Engineer

Los Angeles, CA, US$185,000-$200,000Posted 9 days ago

Job Description

About Fuel Cycle

:

Fuel Cycle empowers leading organizations with agile research solutions that deliver decision-ready insights — fast, flexible, and fully integrated. As a market research disruptor, our AI-powered Insights Platform is built for speed, precision, and scale. With cutting-edge tools and seamless audience connectivity, we help brands ditch the guesswork and make smarter, customer-led decisions at lightning speed.

Why work at Fuel Cycle?

Join a high-growth team where curiosity is valued, ownership is encouraged, and your work drives real-world impact. Whether you’re based at our Los Angeles HQ, New York City hub, working remotely across the U.S., or part of our global team in India, you’ll help shape the future of decision intelligence for some of the world’s most iconic brands.

Overview

We are building the next generation of our platform — an AI-native data foundation that will power intelligent agents, living user profiles, digital twins, and conversational research analytics. This is a greenfield, foundational build that will define the future of the company.

We are building a new data engineering team reporting directly to the VP of Engineering. You will be a founding member of this team, responsible for designing and building the Databricks-first data lake and pipeline infrastructure that every future AI product will depend on.

This is not a maintenance role. We need engineers who are productive from day one — experienced enough to make architectural decisions independently and drive the build without step-by-step direction.

Key Responsibilities

Data Lake & Warehouse Architecture

  • A multi-tenant data lake and warehouse that unifies all research data — surveys, qualitative feedback, CRM, media transcripts, and more — in a structured, AI-consumable format
  • Tenant-isolated data architecture where enterprise client data is structurally separated at the storage and query layer
  • Provenance-aware data...

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