Staff Data Warehouse Engineer

BILL•San Jose, CA

6h•$148,400 - $209,300•Remote

About The Position

Join BILL as a Staff Data Warehouse Engineer and help build the trusted data backbone that powers decision-making across Finance, Product, and Go-to-Market. You’ll be a senior technical owner on our Data Operations & Enablement team, designing and delivering end-to-end pipelines and warehouse architecture that become the single source of truth for the business. If you take pride in building reliable systems the right way, and you enjoy turning ambiguity into well-modeled, performant data products, this is the role to do your career-defining work. In this role, you’ll architect and harden core data infrastructure from ingestion through curated marts that executive leadership and Finance rely on for reporting, planning, and strategic decisions. You’ll partner closely with analytics, data science, and product teams to make integrations robust, patterns reusable, and datasets trustworthy. Bring a builder’s mindset, a bias for simplicity, and a passion for elevating standards. Your work will be the foundation others build on.

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.

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.