> Markdown version of [/jobs/ext/1350079-staff-data-warehouse-engineer](https://www.wearedevelopers.com/jobs/ext/1350079-staff-data-warehouse-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Data Warehouse Engineer - **Company:** Wills and Wills L P - **Location:** San Jose, CA, United States - **Experience:** Expert - **Salary:** $174,600.0 - $209,300.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Software as a Service, Code Review, Databases, Information Engineering, Extract Transform Load (ETL), Data Warehousing, DevOps, Python (Programming Language), Performance Tuning, SQL Databases, Snowflake, Core Data - **Published:** July 19, 2026 - **Apply:** https://www.dice.com/job-detail/29454126-e681-4b69-9a54-3595124f84f0 ## About the Role * 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. ## Description 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., * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)