Senior Data Engineer

Role overview As a Senior Data Engineer on a small analytics team, you’ll own the production data platform from ingestion through warehouse transformations and the semantic models that support business analysis and AI-assisted answers. The focus is on making data accurate, well-tested, understandable, and dependable before building automation on top of it. You’ll work across engineering, finance, product, and go-to-market teams, with broad scope and visible impact.

Responsibilities - Own the warehouse, ingestion, and transformation stack, including architecture, access, CI/CD, cost, standards, and data quality. - Build and operate pipelines from production systems and business tools; manage orchestration, deployments, environments, and incident response. - Maintain dbt models and semantic foundations used by AI agents, and assess whether those agents provide correct answers. - Improve quality and reliability through tests, data contracts, observability, and simpler maintainable models. - Share curated data with business systems and partner with engineering on how source data is produced and changed. - Use AI coding tools in development and establish appropriate access, review, and human verification practices for production data.

Requirements - 5+ years of data engineering experience and a strong software engineering foundation. - Experience building and operating a production data stack across ingestion, warehouse, transformation, and orchestration. - Hands-on dbt expertise, including model design, testing, macros, CI, and refactoring. - Cloud warehouse administration experience, including permissions, performance, and cost management; Snowflake is preferred, with BigQuery or Databricks considered. - Expert SQL, strong data modeling skills, and Python for pipelines, automation, and tools. - Experience with managed ingestion tools and AWS or GCP; familiarity with data contracts or observability tools. - Regular use of AI coding tools, sound judgment about their limitations, and ability to independently investigate and explain business data.

Nice to have - Experience building semantic layers or AI-assisted analytics systems.

Benefits and work setup - U.S. package includes flexible vacation, 11 company holidays, health, dental and vision coverage, 401(k), parental leave, and professional development support. - U.K. package includes 25 days of annual leave plus public holidays, private medical and dental coverage, matched pension, parental leave, and professional development support. - Weekly no-meeting days and quarterly focus weeks; lunch, internet, and equipment support are available. Offices are in San Francisco, New York City, and London.