Data Engineer

FluidStack
Austin, New York, San Francisco, Seattle
Workplace: OnsiteFull timeUSD 269,000 - 317,000 annuallyFunction: Data Analytics & Business IntelligenceSkills: ["Extreme ownership","Velocity","First principles","Love of the game"]

Build production data pipelines that integrate company systems (ERP, ATS, project management, construction software, telemetry) into a single queryable layer. Own the data model behind a live knowledge graph, turning messy vendor and field data (including PDFs/spreadsheets/exports) into structured, trustworthy inputs. Ship datasets and services with SLAs for internal tools, dashboards, and ML models that depend on daily reliability.

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FursaFursa
FluidStack
FluidStack
1 month ago

Data Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build production data pipelines that integrate company systems (ERP, ATS, project management, construction software, telemetry) into a single queryable layer. Own the data model behind a live knowledge graph, turning messy vendor and field data (including PDFs/spreadsheets/exports) into structured, trustworthy inputs. Ship datasets and services with SLAs for internal tools, dashboards, and ML models that depend on daily reliability.
Location: Austin, New York, San Francisco, Seattle
Workplace: Onsite
Employment Type: Full time
Job Function: Data Analytics & Business Intelligence

Key Responsibilities

  • •Build pipelines that pull company systems into one queryable layer.
  • •Own the data model behind the company’s live knowledge graph (sites, equipment, schedules, people).
  • •Ship datasets and services with SLAs for internal tools, dashboards, and ML models.
  • •Turn messy vendor and field data (PDFs, spreadsheets, exports) into structured, trustworthy inputs.

Pay and Benefits

Salary: USD 269,000 - 317,000 annually

Key Requirements

  • •Build and operate production data pipelines that other teams depend on.
  • •Model messy real-world domains into schemas that hold up as the business changes.
  • •Treat data quality as an engineering problem with tests, monitoring, and lineage.
  • •Extract structure from unstructured sources.
  • •Move fast with AI tools and modern data stacks without creating data quality issues.
Experience:AIData pipelinesData engineeringKnowledge graphs
Skills:Extreme ownershipVelocityFirst principlesLove of the game
Tech Stack:PostgresDbtStreamingEventingLLM-based extractionML modelsETLPipelinesKnowledge graphData qualityMonitoringLineageTests

Company Brief

FluidStack
Builds and deploys large-scale GPU cloud infrastructure for AI labs, enterprises and governments, providing high-performance AI training and inference capacity and rapid data-center deployment services.
Industry: Cloud Computing
Company Size: Medium (51 to 250 employees)
Growth: Growth Stage Startup
Funding: Series A
Headquarters: New York, United States
Founded: 2017
Glassdoor
Glassdoor: 4.7
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