About the Role
Uber's Batch Data Platform powers the company's most critical decision-making, analytics, and AI-driven intelligence. We are evolving from traditional data processing toward a
next-generation Data Intelligence Platform- one that unifies batch, streaming, and multimodal data into a cohesive, AI-ready foundation.
As a Senior Staff Engineer, you will design and drive the architecture behind Uber's
Elastic Convergent Compute,
Unified Semantic Layer, and
Self-Evolving Knowledge Platform, enabling real-time insights, trustworthy AI agents, and intelligent business automation at a global scale.
What the Candidate Will Do -
- Architect and evolve Uber's Multi-Modal Data Platform to unify batch, streaming, and AI compute into one elastic, intelligent fabric.
- Partner with AI and Data Agent teams (e.g., QueryCopilot, DataIQ, SODA) to operationalize Agentic Data Intelligence, bridging human validation with autonomous reasoning.
- Drive Uber's next-generation Self-Evolving Knowledge Platform - transforming how knowledge, SOPs, and organizational intelligence are captured, contextualized, and evolved.
- Basic Qualifications -
- Proven experience designing and building large-scale distributed data and AI infrastructure systems, spanning batch, streaming, and model-serving environments (e.g., Spark, Flink, Ray, Presto, Iceberg, Hudi, or similar).
- Deep understanding of data + AI convergence, including how compute fabrics, vector databases, and model-serving platforms integrate with data pipelines and semantic layers.
- Proven experience leading cross-functional engineering initiatives that improve reliability, cost efficiency, and developer velocity across hybrid data and AI ecosystems.
- Strong programming background (Java, Scala, Python, or Go) with solid foundations in distributed systems, performance tuning, and storage architecture.
- Preferred Qualifications -
- Expertise in data intelligence architectures - unified compute fabrics, semantic modeling, and multimodal data processing (structured, semi-structured, unstructured).
- Experience designing AI Infrastructure at scale - including model training/inference pipelines, embedding management, or retrieval-augmented generation (RAG) systems.
- Hands-on work with observability, data freshness, and quality frameworks (SLO/SLA-driven data reliability).
- Demonstrated ability to lead platform modernization efforts, mentor teams, and influence long-term technical strategy across multiple orgs.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.
