Data Engineer

Role overview A fast-growing developer-tools company is hiring a Data Engineer to own and evolve the internal data platform end-to-end, from ingestion and orchestration through modeling, governance, and consumption. Operating on an agent-first OS where AI assistants query the warehouse and open pull requests alongside humans, the team moves quickly, documents in the open, and experiments rapidly. This high-ownership role on a lean team partners with Product Engineering, RevOps, Finance, GTM Engineering, and Security to raise the bar on reliability, correctness, and operational rigor.

Responsibilities

- Own the reliability, freshness, and scaling of ingestion and orchestration pipelines landing source data in Snowflake, including monitoring, alerting, runbooks, and backfill/reprocessing patterns. - Design, build, and scale 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, codify them in the warehouse, and resolve data quality and freshness issues at the source. - Own Snowflake RBAC, dynamic masking, and PII classification for humans, agents, and service accounts, and review DDL and access requests. - Own the reverse-ETL layer and runbooks that deliver warehouse data to Salesforce, Slack, and internal agents, and extend semantic views, context, and evaluations that let agents answer business questions accurately. - Build and advance CI/CD review gates in the data-platform monorepo, including automated review of agent-authored pull requests, and own the infrastructure the platform runs on in partnership with infrastructure engineers.

Requirements

- 5+ 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, plus ingesting data from production databases and SaaS sources with backfill/reprocessing patterns. - Production data-systems

experience: monitoring, alerting, debugging, incident response habits, and pragmatic SLO/SLA thinking. - Experience with warehouse access governance (RBAC, masking policies, PII handling), strong data modeling judgment, and an understanding of schema evolution. - Strong SQL and Python with 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, and translating ambiguous business questions into technical specs. - Comfortable using LLMs and coding agents in day-to-day development, with judgment to validate output and a systems-thinker mindset around freshness, correctness, and failure modes.

Benefits and work setup

- Fully remote working arrangement with healthcare, dental, and vision coverage for employees and family, plus parental leave and paid time off. - 401k matching, competitive equity, FSA, short- and long-term disability, voluntary life, fertility benefits, 20 days paid vacation plus 10 holidays and unlimited sick leave, 12 weeks fully paid parental leave, monthly fitness and wellness stipends, commuter benefits for hybrid employees in SF/NYC, and unlimited token usage.