Staff Data Engineer, Tech Foundations

What you'll do

• Lead the architecture, implementation, and operation of high-impact data pipelines for AI usage, Unit Economics, and financial metrics.
• Build reliable ingestion and transformation pipelines for non-platform systems like Jira and other enterprise applications.
• Translate ambiguous business requirements into clear source contracts, reusable fact and dimension models, and technical designs.
• Develop configurable pipelines and shared components to simplify onboarding new data sources and products.
• Establish automated testing, reconciliation, anomaly detection, and monitoring to ensure data accuracy and availability.
• Optimize distributed processing, storage, and query performance to improve data freshness and reduce compute costs.
• Own production reliability through on-call participation, incident response, and continuous improvements to systems and runbooks.
• Shape the technical roadmap, lead design reviews, and mentor engineers on shared data engineering practices.

What we're looking for

• 9+ years of relevant industry experience with a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
• 6+ years of relevant experience with a PhD.
• Track record of leading complex data engineering initiatives from ambiguous requirements through architecture, delivery, and production ownership.
• 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.
• Strong data modeling skills including fact and dimension design, slowly changing dimensions, and historical data management.
• Experience establishing data quality controls, observability, lineage, governance, and incident recovery practices.
• Experience with AI usage or cost measurement, Unit Economics, or financial datasets (preferred).