Collective
AI Data Engineer, Data Platform
$180K–$230K
San Francisco · Hybrid · Full-time · Posted Sep 24, 2026
- Experience
- 5+ years; data engineering, analytics engineering, or a closely related role.
About the job
Own and scale Collective’s data platform by building reliable pipelines and models that support analytics, reporting, and AI.
What you'll do
- Build and maintain pipelines from product, financial, SaaS, and external systems into BigQuery, and develop documented analytical models.
- Own data quality, reliability, security, performance, and engineering standards across the data platform.
- Support analytics and AI by maintaining semantic layers, metric definitions, and documentation for reliable warehouse queries.
What they ask for
- 5+ years of professional experience in data engineering, analytics engineering, or a closely related role.
- Expert-level SQL and strong Python skills for tested, production-grade pipelines, transformations, and tooling.
- Production experience with a cloud data warehouse, a transformation framework such as dbt, managed ingestion tools, and an orchestrator.
- Experience with data modeling, pipeline quality and observability, and software engineering practices including code review and CI/CD.
Nice to have
- Experience with streaming or event data and product analytics tooling.
- Experience with Terraform, Google Cloud Platform, financial data, semantic layers for LLM tools, or AI-assisted development.
Pay
$180K – $230K (base salary); Offers Equity; Offers Bonus
Tools
BigQuery, Fivetran, Python, dbt, Metabase, Airflow, Dagster, Cloud Composer
AI focus
Maintain the semantic layer, metric definitions, and documentation so LLM-based tools and internal agents can query the warehouse accurately; experience supporting LLM evaluation programs is a nice-to-have.
Model-written summary · the original posting is authoritative