Senior Staff Software Engineer , Data Platform

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.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.