Staff Data Warehouse Engineer

BILL is a fintech company that provides financial automation tools for businesses. The Staff Data Warehouse Engineer will own end-to-end data pipelines and warehouse architecture, administer and optimize core data infrastructure, and create trusted data products for Finance, Product, and Go-to-Market teams. The role also involves establishing engineering standards, mentoring engineers, and designing warehouse models for accurate AI-agent querying.

Responsibilities:

• Own end-to-end delivery of pipelines and warehouse architecture, from design through production, for new builds, migrations, and re-platforming efforts
• Administer and harden the data warehouse, including schema design, performance tuning, stability, and cost-aware optimization
• Embed data quality and governance into pipelines by default — testing, documentation, lineage — not as afterthoughts
• Translate ambiguous business requirements into clear technical designs; scope tradeoffs and dependencies with cross-functional stakeholders
• Define and codify simple, stable, repeatable engineering standards and patterns adopted by the broader team
• Mentor engineers through design reviews, code reviews, and hands-on guidance to raise the technical bar
• Evaluate and introduce tools or architecture patterns when they materially improve scale, reliability, or cost and be able to justify and explain the rationale
• Design the warehouse to be queried by AI agents, not just people. This means structuring models, naming conventions, and metadata so natural-language querying returns correct results, and authoring the skill files that let AI tools query the warehouse safely and accurately rather than guessing at intent

Requirements:

• 8+ years of experience in data engineering or combined software/data engineering roles, with a track record of owning significant warehouse builds end-to-end
• Expert-level SQL (multiple dialects) and strong Python, with examples of production-grade applications beyond ad hoc scripts
• Deep knowledge of ETL/ELT design, ingestion methods, and orchestration (e.g., dbt, Airflow or equivalents)
• Hands-on experience with modern lakehouse/warehouse platforms (e.g. Snowflake, Trino/Starburst, or similar) and understanding of engine tradeoffs
• Experience in financial services and/or SaaS environments
• Comfort operating with minimal DevOps/IT support on core database and warehouse administration
• Proven mentorship and standards-setting experience; formal management not required
• Applicants must have authorization to work in the United States without requiring visa sponsorship now or in the future