Staff Software Engineer- Data Platform Engineering

Business Area: Professional Services Seniority Level: Mid-Senior level Job Description:  At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry.  Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises. The Leading Emergent Engineering Taskforce (LEET) is a new, agile operational unit designed to execute on Cloudera’s most critical strategic initiatives. Operating as an "empowered pod," we bridge the gap between abstract requirements and real-world execution, tackling both complex customer integrations and high-impact internal engineering projects. We move with the velocity of a startup while leveraging the massive scale of the Cloudera Data Platform. We are looking for a Staff Software Engineer with strong enterprise data platform experience to help evolve Cloudera’s hybrid data and AI platform. In this role, you will design and build software capabilities for large-scale data workloads and distributed systems. You will bring expertise in how enterprise data platforms are built and operated in production, and apply that knowledge to solve complex engineering challenges across data processing, storage, and cloud-native environments. This role is ideal for an engineer who enjoys working on challenging distributed systems problems, understands enterprise data workflows, and wants to influence the evolution of a leading hybrid data platform. As a Staff Software Engineer you will work on: Data Platform Engineering: Design, develop, and improve software capabilities that enhance Cloudera’s data platform. Build solutions for large-scale data processing, analytics, and AI-enabled workloads. Apply expertise in enterprise data architectures and workflows to solve complex platform challenges. Contribute to the evolution of a hybrid data platform operating across on-premises and public cloud environments. Distributed Systems & Cloud-Native Engineering: Build reliable and scalable software for distributed data workloads. Solve complex engineering challenges involving scalability, performance, reliability, concurrency, and fault tolerance. Work with cloud-native technologies and containerized environments. Debug complex issues across application, runtime, storage, and networking layers. Product Innovation & Collaboration Partner with engineering, product, and field teams to understand real-world platform challenges and identify opportunities for improvement. Translate technical insights into scalable engineering solutions and product capabilities. Prototype and evaluate approaches to emerging data and AI platform needs. Technical Leadership Provide technical leadership through architecture discussions and engineering decisions. Influence technical direction and contribute to engineering best practices. Mentor engineers and help build a strong engineering culture. We’re excited about you if you have: 8+ years of software engineering experience building and delivering production systems. Strong programming skills in Java, Scala, Go, or similar languages. Experience building, operating, or extending enterprise data platforms, distributed data engines, or large-scale data processing systems (e.g., Apache Spark, Trino, Hive, Iceberg, or distributed storage systems). Hands-on experience running distributed workloads in containerized and cloud-native environments, with practical experience using Kubernetes. Solid understanding of distributed systems principles, including scalability, reliability, concurrency, and fault tolerance. Ability to collaborate effectively across engineering, product, and field teams. You may also have: Strong understanding of database internals, including query execution, query optimization, indexing, or columnar storage formats such as Parquet and ORC. Experience building or operating enterprise data platforms across hybrid environments (on-premises and public cloud). Experience supporting AI/ML workloads built on enterprise data platforms. Open-source contributions to big data or cloud-native infrastructure projects. Experience working with enterprise customers on complex technical challenges. What you can expect from us: Generous PTO Policy  Support work life balance with Unplugged Days Flexible WFH Policy  Mental & Physical Wellness programs  Phone and Internet Reimbursement program  Access to Continued Career Development  Comprehensive Benefits and Competitive Packages  Paid Volunteer Time Employee Resource Groups EEO/VEVRAA #LI-RC1