The opportunity
The Data team at WorkOS plays a central role on the company operations to ensure information and insights are accurate and available from any surface, whether that's a visualization tool or an agent's response, to accelerate company growth and scale. The team owns WorkOS's…
What you'll do
Own the reliability, freshness, and scaling of the ingestion and: orchestration pipelines that land source data in Snowflake, including monitoring, alerting, runbooks, and backfill and reprocessing patterns
Design, build, and scale the core dbt models (Bronze, Silver, Gold) for: billing and usage, CRM, product events, and GTM funnel reporting
Partner with Product, Finance, RevOps, and GTM to define metrics and codify: them in the warehouse, and diagnose and resolve data quality and freshness issues at source, not just downstream
Own Snowflake RBAC, dynamic masking, and PII classification for humans,: agents, and service accounts, so sensitive data is protected without blocking legitimate use, and review DDL and access requests from Engineering and GTM
Own the reverse-ETL layer and the runbooks that deliver warehouse data to: Salesforce, Slack, and internal agents
Extend the semantic views, context, and evaluations that let agents answer: business questions accurately, and expand what agents can operate directly, from runbooks and ingestion to pull requests
What they're looking for
- + years (or equivalent) building and operating production data platforms, including the transformation layer
- Deep experience with Snowflake, dbt, and an orchestrator such as Prefect,: Airflow, or Dagster, and with ingesting data from production databases and SaaS sources, including backfill and reprocessing patterns
- Experience running data systems in production: monitoring, alerting, debugging, incident response habits, and pragmatic SLO/SLA thinking
- Experience with warehouse access governance: RBAC, masking policies, and PII handling
- Strong data modeling judgment and an understanding of schema evolution
- Strong SQL and Python; disciplined engineering practices (tests, docs, reviews, CI/CD)
- Proven experience operating as the only engineer on a layer, balancing: foundational architecture with urgent business needs
- Working knowledge of how GTM, Finance, and Product teams operate in addition: to working with Engineering, and experience translating ambiguous business questions into technical specs
