Jobs / Fue***
Senior Data Engineer
Fue*** · Los Angeles, CA, United States
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Los Angeles, CA, United States185,000-200,000 USD/yearlyRemote
Remuneration
185,000-200,000 USD/yearly
Location
Los Angeles, CA, United States
Visa sponsorship
Sponsors visa
Job summary
About Fue***: Fue*** 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.
Benefits
Fuel Cycle is committed to supporting the well-being, flexibility, and growth ofWe offer a competitive and inclusivePackage that includes:Comprehensive Health Coverage: Medical, dental, and vision insurance plans401(k) with Company Match: Plan for your future with our retirement savings progEquity Purchase Option: Participate in Fuel Cycle’s long-term successFlexible Work Schedule: Empowering you to balance life and workGenerous Time Off:15 vacation days and 7 sick days per year12 company holidays4 floating holidays/recharge days to rest or celebrate what matters to youPaid Parental Leave: Time to bond with your growing family
Qualifications
- 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.
- 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
- Final base salary will be determined based on a variety of factors, including location, work experience,
Responsibilities
- 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.
- 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
Skills
CommunicationSalesforce
Degrees
Associate
Industry
EducationEnergyHealthcareInsuranceLogisticsMediaSaas
Company size
Enterprise