Staff Data Engineer

About the role

The Staff Data Engineer will serve as the senior technical leader for our data platform. They will own the architecture and reliability of the pipelines that move data across the business, set the technical bar for the engineers around them, and build the platform foundations that our analytics, reporting, and AI agents depend on.

Responsibilities

• Own the architecture of our data platform, spanning ingestion (Hevo, Estuary), our Google BigQuery warehouse, and the dbt transformation layer — designing systems that are scalable, reliable, secure, and built to last.
• Set the technical bar as a senior IC, leading through design reviews, code review, and mentorship — raising the quality, rigor, and engineering discipline of the team without a formal management role.
• Develop end-to-end with AI coding agents. Our teams build with Claude Code and similar tools, and you'll help define the practices, guardrails, and standards that make AI-assisted engineering fast, safe, and high-quality.
• Invest in reliability and observability, establishing testing, monitoring, alerting, and incident-response practices so data lands on time, is trusted, and failures are caught before stakeholders notice.
• Lay the foundations for agentic analytics, building the well-modeled, well-governed platform that agents and MCP connections rely on to deliver trustworthy answers from data.
• Partner with analytics engineers, analysts, and stakeholders to understand data needs, unblock high-value use cases, and translate business requirements into durable platform capabilities.
• Engineer tooling and services beyond the warehouse - building the APIs, automated jobs, and internal tools in Python that make the platform run smoothly and put data in more people's hands than SQL alone can reach.
• Drive the evolution of our warehouse architecture - leading hands-on POCs on lakehouse patterns, open table formats, and alternative query engines, and deciding what's worth adopting next.

Requirements

A seasoned data engineer with 8+ years building data platforms and pipelines in production, with a track record of technical leadership at the staff or senior level. Expert in the modern data stack, systems thinker, fluent in AI-assisted development, reliability-obsessed, governance-minded without being risk-averse, a force multiplier, technically fluent and a clear communicator, cloud-infrastructure fluent, and a forward-thinking architect.

Qualifications

Experience with cloud data warehousing (BigQuery or equivalent), dbt, and modern ingestion tooling. Strong opinions, loosely held, about when to buy versus build. Fluent in AI-assisted development. Reliability-obsessed. Governance-minded without being risk-averse. Technically fluent and a clear communicator. Cloud-infrastructure fluent. Forward-thinking architect.

Skills

SQL, Python, version control, CI/CD, testing workflows, technical decision-making, cloud infrastructure, data warehousing, data pipeline design, data platform architecture, data governance, data security, data privacy, data quality, data reliability, data observability, data observability, data security, data privacy, data quality, data reliability, data observability, data security, data privacy, data quality, data reliability, data observability, data security, data privacy, data quality, data reliability, data observability, data security, data privacy, data quality, data reliability, data observability, data security, data privacy, data quality, data reliability, data observability, data security, data privacy, data quality, data reliability, data observability, data security, data privacy, data quality, data reliability, data observability, data security, data privacy, data quality, data reliability, data observability, data security, data privacy, data quality, data reliability, 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