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About
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. 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 models where every data point carries full traceability back to its source Data Ingestion & Pipelines Batch ingestion pipelines that migrate and continuously sync data from existing relational databases and cloud storage into the new lake architecture A nightly profile enrichment pipeline that rebuilds living user profiles from all data sources within each client account Data Access & AI Enablement Data access layers serving AI agents via MCP, qualitative search via RAG pipelines, statistical computation tools, REST APIs, and bulk export Your Success Metrics
Quickly integrates with the engineering team and contributes meaningfully to the data platform build Takes ownership of assigned pipeline and infrastructure work end-to-end, from design through production Brings architectural recommendations and solutions proactively, rather than waiting for direction Demonstrates strong collaboration and communication across engineering and product teams Who You'll Work With?
VP of Engineering — your direct manager and the data engineering team's founding sponsor Peer Senior Data Engineers on the founding data engineering team AI product and platform engineers consuming the data foundation you build Product and engineering stakeholders across the Fuel Cycle platform Core Skills, Competencies & Attributes
Proactive Ownership:
You bring recommendations and solutions to your manager — you don't wait to be told what to do. Architectural Judgment:
You have the judgment to make the right foundational decisions and defend them. Greenfield Builder:
You thrive on greenfield builds and take full ownership from design through to production. Comfort with Ambiguity:
You are comfortable with ambiguity and can translate high-level vision into a concrete engineering plan. Outsized Impact:
You understand that on a small team your decisions have outsized and lasting impact. What You'll Bring
You have 5+ years of deep, hands-on experience building production lakehouses on Databricks. You write clean PySpark and Python, model data thoughtfully, and know how to build for a multi-tenant SaaS environment. Deep production experience across the Databricks platform including Unity Catalog, Delta Live Tables, Databricks SQL, and Workflows Delta Lake as a production table format — ACID transactions, schema evolution, performance optimization, and multi-tenant governance via Unity Catalog Experience building and maintaining dbt transformation projects using the Databricks adapter in a production environment PySpark for large-scale data transformation and batch pipeline authoring Strong understanding of batch ingestion pipeline design — migrating from relational sources like MySQL and PostgreSQL into a lakehouse architecture Experience with a modern pipeline orchestrator such as Dagster, Prefect, or Databricks Workflows; Dagster experience is a strong positive Familiarity with vector databases, embedding pipelines, and RAG patterns for AI workloads — using tools such as Databricks Vector Search, pgvector, or Amazon OpenSearch Exposure to AI agent and LLM-serving infrastructure including Amazon Bedrock, AgentCore, and Strands Experience with data cataloging and governance tools such as Unity Catalog or OpenMetadata Data modeling for multi-tenant analytical workloads — partitioning strategy, schema design, and tenant isolation patterns Databricks on AWS — workspace configuration, S3 integration, IAM, and cost governance Infrastructure as code using Databricks Asset Bundles or Terraform Strong Python and SQL skills Preferred, but Not Required
Databricks certifications — Data Engineer Associate or Professional Salesforce or CRM data integration experience Prior experience in a multi-tenant SaaS environment with strict data isolation requirements Experience migrating from OLTP to a lakehouse architecture AWS-Native Experience — A Strong Positive
Candidates with experience in AWS-native data services are strongly valued. Engineers who understand both Databricks and AWS-native approaches bring a broader architectural perspective that helps the team make better long-term platform decisions. Apache Iceberg, AWS Glue, Athena, and DynamoDB experience Benefits & Perks
Fuel Cycle is committed to supporting the well-being, flexibility, and growth of our team. We offer a competitive and inclusive benefits package that includes: Comprehensive Health Coverage:
Medical, dental, and vision insurance plans 401(k) with Company Match:
Plan for your future with our retirement savings program Equity Purchase Option:
Participate in Fuel Cycle's long-term success Flexible Work Schedule:
Empowering you to balance life and work Generous Time Off: 15 vacation days and 7 sick days per year 12 company holidays 4 floating holidays/recharge days to rest or celebrate what matters to you Paid Parental Leave:
Time to bond with your growing family Monthly Internet & Phone Stipend:
Support for remote work setup Wellness & Lifestyle Perks:
Access to tools like
Rightway (healthcare navigation), Headspace (mental wellness), Peloton (fitness) , and more Team Connection Perks: Weekly community lunches:
Refreshments and snacks at our LA & NY headquarters Pet-friendly office environments Compensation Overview
The expected starting salary range for this position is
$185,000 - $200,000.
This range represents the typical starting compensation offered to candidates hired into this role. Final base salary will be determined based on a variety of factors, including location, work experience, skills, knowledge, education, and certifications. This role may also be eligible for an equity grant or purchase option. These components make up your total compensation package, which will be reviewed in greater detail during your initial recruiter conversation.
Languages
- English
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