Lead Data Engineer
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Requirements
• 5+ years in data engineering with 2+ years leading projects • Expert SQL and Python with deep experience building production pipelines at scale • Hands-on with dbt and a workflow manager such as Airflow or Prefect • Strong background in dimensional and event-driven modeling and a company-wide metrics layer • Experience with Snowflake or BigQuery, plus Postgres for transactional use cases • Track record building data products for analytics and customer reporting • Cloud experience on AWS or GCP and infrastructure as code such as Terraform • Domain experience in SEO, content analytics, or growth experimentation is a plus • Clear communicator with a bias for action, curiosity, and a high bar for quality • Our Guiding Principles • Extreme Ownership • Curiosity and Play • Make Our Customers Heroes • Respectful Candor
Responsibilities
• Data platform ownership: design, build, and operate batch and streaming pipelines that ingest data from crawlers, partner APIs, product analytics, and CRM. • Core modeling: define and maintain company-wide models for content entities, search queries, rankings, AI agent answers, engagement, and revenue attribution. • Orchestration and CI: implement workflow management with Airflow or Prefect, dbt-based transformations, version control, and automated testing. • Data quality and observability: set SLAs, add tests and data contracts, monitor lineage and freshness, and lead root cause analysis. • Warehouse and storage: run Snowflake or BigQuery and Postgres with strong performance, cost management, and partitioning strategies. • Semantic layer and metrics: deliver clear, documented metrics datasets that power dashboards, experiments, and product activation. • Product and customer impact: partner with Product and Customer teams to define tracking plans and measure content impact across on-site and off-site channels. • Tooling and vendors: evaluate, select, and integrate the right tools for ingestion, enrichment, observability, and reverse ETL. • Team leadership: hire, mentor, and level up data and analytics engineers; establish code standards, review practices, and runbooks.
Benefits
• Equity in a fast-growing startup • Competitive benefits package tailored to your location • Flexible time off policy • A fun-loving and (just a bit) nerdy team that loves to move fast!