AI Data Engineer, Data Platform

Collective
San Francisco
Workplace: HybridFull timeUSD 180,000 - 230,000 annuallyFunction: Data Science & Machine LearningExperience: 5+ yearsSkills: ["Data ownership","Communication","Stakeholder alignment","Problem-solving","Documentation"]

Own and scale the data platform that powers Collective’s analytics, reporting, and AI. Design and build scalable batch and event-driven pipelines into a BigQuery warehouse, model data with dbt, and ensure reliability through testing, monitoring, alerts, and data contracts. Optimize BigQuery performance and cost, establish engineering standards (CI/CD, code review, IaC), and govern secure, compliant data access while partnering across product, analysts, and stakeholders.

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FursaFursa
Collective
Collective
1 day ago

AI Data Engineer, Data Platform

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Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Own and scale the data platform that powers Collective’s analytics, reporting, and AI. Design and build scalable batch and event-driven pipelines into a BigQuery warehouse, model data with dbt, and ensure reliability through testing, monitoring, alerts, and data contracts. Optimize BigQuery performance and cost, establish engineering standards (CI/CD, code review, IaC), and govern secure, compliant data access while partnering across product, analysts, and stakeholders.
Location: San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design and build scalable batch and event-driven data pipelines ingesting from application databases, SaaS tools, and external APIs into BigQuery using managed connectors and custom Python loaders.
  • •Model and implement dimensional and analytical data models in dbt using a layered architecture (raw, staging, marts) with documentation and consistent grains and naming.
  • •Own data quality and reliability by implementing testing, monitoring, alerting, data contracts, and triaging pipeline failures and incidents.
  • •Optimize warehouse performance and cost through query tuning, partitioning and clustering, and managing BigQuery spend as data volume grows.
  • •Establish and drive data engineering standards (version control, code review, CI/CD, infrastructure-as-code) and govern secure data access with PII handling and retention practices.

Pay and Benefits

Salary: USD 180,000 - 230,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVision401kEquityPaid LeaveParental Leave

Key Requirements

  • •5+ years of professional experience in data engineering, analytics engineering, or a closely related role, ideally at a B2B SaaS or fintech company.
  • •Expert-level SQL and strong Python skills for building production-grade pipelines and transformations.
  • •Hands-on experience with a cloud data warehouse (BigQuery preferred), dbt (or equivalent), managed ingestion tools like Fivetran, and an orchestrator.
  • •Deep understanding of dimensional modeling, layered warehouse architecture, and schema design (grain, naming, consistency).
  • •Experience implementing testing, monitoring, alerting, and operating data pipelines in production including on-call.
Experience:5+ yearsB2B SaaSFintech
Skills:Data ownershipCommunicationStakeholder alignmentProblem-solvingDocumentation
Tech Stack:BigQueryPythonSQLDbtFivetranAirflowDagsterCloud ComposerMetabasePub/SubKafkaAmplitudeTerraformGoogle Cloud PlatformDatadogGitCI/CDInfrastructure-as-codeLLMSemantic layer

Company Brief

Collective
Provides an all-in-one online back-office platform for solopreneurs, offering company formation, payroll, bookkeeping, tax services, and financial advisory via AI-assisted tools and a concierge team.
Industry: SaaS
Company Size: Medium (51 to 250 employees)
Growth: Growth Stage Startup
Funding: Series C
Headquarters: San Francisco, United States
Founded: 2020
Glassdoor
Glassdoor: 4.2
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