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Staff Data Engineer, Tech Foundations
San Francisco, CA · Staff · Full-time · Posted Oct 16, 2026
- Experience
- 9+ years of relevant industry experience with a Bachelor’s or Master’s degree, or equivalent practical experience; or 6+ years of relevant experience with a PhD.
- Education
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience; or a PhD for the 6+ years experience alternative.
About the job
Leads the architecture, delivery, and production operation of reusable data systems for AI usage and cost, Unit Economics, enterprise applications, and financial metrics.
What you'll do
- Lead data pipeline initiatives from requirements and design through implementation, validation, and production ownership.
- Build dependable, reusable data models and ingestion frameworks; improve data quality, performance, freshness, and cost efficiency.
- Set technical direction, mentor engineers, and coordinate with business and engineering stakeholders.
What they ask for
- Deep expertise in SQL and strong programming skills in Python or Scala.
- Extensive experience with distributed processing technologies such as Apache Spark and large-scale analytical storage systems.
- Track record leading complex data engineering initiatives from ambiguous requirements through delivery and sustained production ownership.
- Experience with data modeling, heterogeneous source integration, reliable pipelines, data quality, migrations, and performance optimization.
Nice to have
- Experience with AI usage or cost measurement, cloud cost attribution, Unit Economics, enterprise application data, or financial and payments datasets.
- Familiarity with workflow orchestration, SQL transformation frameworks, and modern table formats such as Apache Iceberg.
Tools
SQL, Python, Scala, Apache Spark, Apache Iceberg
AI focus
Build datasets and models to measure organizational AI adoption, usage, consumption, and spending, including costs.
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