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Uber

Sr Software Engineer - Streaming Data Platform

Sunnyvale, CA, United States
San Francisco, CA, United States
Seattle, WA, United States

$202,000 to $224,000 USD / year

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Job details

Pay: $202,000 to $224,000 USD / year
Posting language: English
Posted: Nov 5, 2026

Original job description

About the role and team Leading at Uber means setting technical direction and building foundational systems that operate at global scale. As a Sr Software Engineer on the Streaming Data Platform team, you will shape the architecture and evolution of the critical infrastructure that powers real-time data movement and processing across Uber's global marketplace. Our streaming data platform serves as the backbone for real-time applications, analytics, and machine learning, enabling engineering teams to reliably produce, process, and consume massive volumes of data. The platform supports a diverse range of mission-critical workloads, where scalability, low latency, high availability, and operational efficiency are essential. You will tackle some of the most challenging problems in large-scale distributed systems, from designing next-generation streaming architectures and improving fault tolerance to optimizing resource utilization and simplifying platform operations. Your work will directly influence the reliability, efficiency, and developer experience of foundational infrastructure used across Uber. This role is for an accomplished technical leader who can navigate complex architectural tradeoffs, anticipate future scaling challenges, and drive transformative engineering initiatives across organizational boundaries. You will combine deep technical expertise with strategic thinking, influence long-term technology investments, and empower other engineers to deliver impactful solutions. If you are passionate about solving hard distributed systems problems, pushing the boundaries of infrastructure performance, and building platforms that enable innovation at unprecedented scale, this is where you will make your mark. What you'll do

Define and drive the technical vision and architecture for Uber's streaming data platform, ensuring its long-term scalability, reliability, performance, and extensibility as business and infrastructure requirements evolve.
Lead the design and evolution of large-scale distributed streaming systems, solving fundamental challenges in data delivery, distributed coordination, consistency, fault tolerance, resource management, and high availability.
Drive architectural innovation and modernization across streaming infrastructure, identifying opportunities to simplify complex systems, eliminate scalability bottlenecks, and improve overall platform efficiency.
Establish technical strategies for performance, reliability, and cost efficiency, leveraging deep systems expertise, benchmarking, and workload analysis to optimize compute, storage, memory, and network utilization.
Architect highly resilient, multi-tenant infrastructure that supports diverse workloads with demanding throughput, latency, durability, and availability requirements.
Build and champion foundational platform capabilities, including automation, observability, capacity management, and self-service tooling, that improve developer productivity and reduce operational complexity across engineering organizations.
Anticipate emerging technical challenges and opportunities, evaluating new technologies and architectural approaches to inform strategic investments and long-term platform roadmaps.
Provide technical leadership for complex, cross-organizational initiatives, driving alignment among stakeholders and ensuring successful execution from initial strategy through production adoption.
Establish engineering excellence and operational best practices for mission-critical infrastructure, including architecture reviews, reliability standards, incident prevention, and systematic root-cause analysis.
Mentor and elevate senior engineers, fostering technical depth, sound architectural judgment, and a culture of continuous learning, innovation, and engineering excellence.
Collaborate with infrastructure, storage, data engineering, and product engineering organizations to align platform capabilities with Uber's evolving real-time data needs and broader technical strategy.

Basic Qualifications

6+ years of professional software engineering experience, with significant expertise in designing, building, and operating large-scale distributed systems, infrastructure platforms, or data-intensive services.
Deep understanding of distributed systems principles, including consistency, replication, consensus, fault tolerance, concurrency, distributed coordination, and failure recovery.
Proven experience architecting high-performance, highly available systems that operate at significant scale with stringent throughput, latency, reliability, and durability requirements.
Strong proficiency in one or more systems or backend programming languages, such as Java, Go, C++, Scala, Python, or Rust, with demonstrated ability to design and implement complex production systems.
Experience with large-scale data infrastructure, distributed messaging systems, stream processing platforms, or related technologies, including the ability to reason about their architectural tradeoffs.
Demonstrated track record of providing technical leadership for complex, multi-team engineering initiatives, from architecture and technical strategy through implementation and production adoption.
Strong expertise in system performance analysis, scalability engineering, and troubleshooting complex distributed infrastructure under production workloads.
Proven ability to identify fundamental architectural challenges, evaluate alternative solutions, and make sound technical and business tradeoffs with long-term organizational impact.
Experience influencing technical direction, establishing engineering standards, and driving alignment across teams and organizational boundaries.
Ability to mentor senior engineers, communicate complex technical concepts clearly, and raise the technical bar across an engineering organization.
Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.

Preferred Qualifications

Deep experience architecting or developing large-scale streaming, messaging, or real-time data processing infrastructure using technologies such as Apache Kafka, Apache Pulsar, Apache Flink, Apache Spark, or equivalent distributed systems.
Expertise in the internals of distributed data systems, including partitioning, replication, log-based storage, metadata management, state management, backpressure, and end-to-end delivery guarantees.
Experience leading architectural evolution or significant modernization of foundational distributed infrastructure serving large numbers of applications and engineering teams.
Strong understanding of systems-level performance optimization, including Linux internals, multithreading, memory management, network protocols, storage I/O, and resource scheduling.
Experience designing multi-region or geographically distributed infrastructure, including cross-region data replication, disaster recovery, and availability strategies.
Expertise in building scalable multi-tenant platforms, including workload isolation, capacity management, resource allocation, and infrastructure cost optimization.
Experience with cloud-native infrastructure, container orchestration, and large-scale automation frameworks.
Familiarity with modern data architectures, including change data capture (CDC), event-driven systems, stream processing, real-time analytics, and data lake integration.
Experience designing or contributing to open-source distributed systems, infrastructure frameworks, or technologies adopted by the broader engineering community.
Demonstrated success in driving major architectural transformations, influencing organization-wide technology strategy, and balancing short-term delivery with long-term infrastructure investments.
Advanced degree (Master's or PhD) in Computer Science or a related field, with a focus on distributed computing, storage systems, or system performance.

For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

Ready to Ride?

This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.

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.

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More about this job

Skills

Leadership
Root cause analysis
Data engineering
Programming languages
Oracle Java
Go
C++
Scala
Python
Rust
Troubleshooting
Computer science
Process data
Apache Kafka
Pulsar
Apache Spark
Linux
Scheduling
Implement ICT recovery system
Distributed computing
Collaboration

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