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Senior Software Engineer (Backend) - Data & Storage Platforms

United States, Seattle, Washington Employment contract 202000.00 - 224000.00 USD / Year · Job Posted May 30, 2026
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Job Description

As a Senior Software Engineer in the Storage, Search, and Data (SSD) group, you will be at the heart of Uber’s transition to a Cloud-Native Data Platform. We are moving away from traditional data processing toward a unified, elastic fabric that powers everything from exabyte-scale analytics to the Agentic AI that drives Uber’s future. In this role, you will take ownership of business-critical systems—whether that’s scaling our Distributed MySQL footprint, optimizing Hudi-based Data Lakes, or building the storage layer. You are a Full-Stack Infrastructure engineer: someone who can write high-performance code, design resilient distributed systems, and ensure operational excellence for Tier-0 services that handle millions of concurrent trips.

Job Responsibility

  • Own & Execute: Lead the design and implementation of major features for Uber’s storage and data platforms (e.g., Docstore, Pinot, or OpenSearch)
  • Cloud-Native Modernization: Build and optimize services that leverage GCP and OCI Object Storage, focusing on high-throughput metadata management and S3-compatible API support
  • Storage Optimization: Drive efficiency across our HDFS and Blobstore layers, using table formats like Apache Hudi or Iceberg to improve data freshness and reduce cost
  • AI/ML Integration: Work with AI teams to design high-performance data pipelines, ensuring our storage layers can handle the intense IO demands of GPU-based model training
  • Operational Leadership: Ensure 99.99% availability for your services. You will lead root-cause analyses (RCAs), improve observability, and mentor L3/L4 engineers on best practices for distributed systems

Requirements

  • 5+ Years of Engineering Experience: Proven track record of building and maintaining large-scale distributed systems
  • Deep Storage Knowledge: Practical, hands-on experience with: Relational & NoSQL: Distributed MySQL, Cassandra, or Redis
  • Batch & Object: HDFS, S3/GCS, and Metadata services
  • Distributed Systems: If you’ve worked on systems like Google Spanner or TiDB, you’ll be a great fit for our Transactional Storage (Docstore) team
  • Coding Mastery: Expert-level proficiency in Java, Go, or C++, with a strong focus on concurrency, memory management, and performance tuning
  • Query Engines: Experience with large-scale analytical engines like Presto, Hive, or Trino

Nice to have

  • Lakehouse Innovation: Experience with Apache Hudi, Iceberg, or Delta Lake for optimizing Big Data storage
  • Cloud Infrastructure: Deep familiarity with OCI or GCP and strategies for resource efficiency (the E40 initiative)
  • AI/ML Awareness: Understanding how data storage interacts with ML frameworks like Ray or PyTorch
  • Open Source Contribution: Active participation in community projects like Apache Pinot, Kafka, or Flink
  • Academic-Grade Engineering: Ability to apply research-level concepts (partnering with CMU, Berkeley, or MIT) to solve real-world distributed consensus or indexing challenges

What we offer

  • Uber's bonus program
  • equity award & other types of comp
  • 401(k) plan
  • various benefits

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