Data Engineer

Responsibilities

• 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
• Build and advance the CI/CD review gates in the data-platform monorepo, including the automated review that agent-authored pull requests pass through
• Own the infrastructure the data platform runs on: the compute, deployments, secrets and access patterns, and environments behind ingestion and orchestration, with attention to availability and failure modes, in partnership with our infrastructure engineers
• Example problems you might work on, possible paths rather than a fixed roadmap
• Standardizing how Postgres and SaaS sources are ingested, and consolidating end-to-end pipeline deployment and orchestration in Prefect

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