Sr Staff Engineer

Sr Staff Engineer Department: Engineering Team: Backend Location: Bangalore, India Type: Full-Time **About the Role** The Delivery Data Solutions (DDS) team constructs the foundational technology for Uber’s global delivery ecosystem, ensuring data quality and enhancing app and product performance. We are strategically evolving our data infrastructure, leveraging Generative AI (GenAI) and intelligent data systems to deliver smarter automation, adaptive insights, and faster decision-making for ML and Data Science teams. As a Senior Staff Data Engineer, you will define and drive the architecture, scalability, and intelligence of Uber's delivery data systems. You will lead critical cross-organizational initiatives that govern how Uber ingests, models, secures, and governs delivery data at a global scale. Success in this role requires exceptional technical depth, architectural vision, and the ability to influence engineering and AI domains across complex ecosystems (e.g., merchant, eater, trip, feed, and search). **What the Candidate Will Need / Bonus Points** 1. Build Data Products for business use cases - batch & real time 2. Metrics development for the analytical needs 3. Optimizations & improvements focussed on optimal resource utlization, improve SLA and adhere to the data quality standards. 4. Mentor the fellow engineers on design & architecture, perform quality code review and design reviews for the data product development. 5. Contribute to the strategic investments both from inception and execution point of view. 6. Consult and advise the product engineering teams on the data engineering practices. \-\-\-\- Basic Qualifications ---- 01. Bachelor’s or Master’s degree in Computer Science or related field. 02. 15+ years of experience building and managing large-scale distributed data systems. 03. Experience implementing GenAI or LLM-driven solutions for data enrichment, automation, or observability use cases. 04. Proficiency in multiple programming languages — Go, Java, Python, or Scala — and data stores such as MySQL, Cassandra, or Redis. 05. Proven exper