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Lead the Cloudera Data Engineering Spark experience for all customers using Cloudera Data Services, Machine Learning services, and more. This high-impact IC role offers the opportunity to shape the future of Cloudera’s Spark space across multiple cloud environments, impacting thousands of customers worldwide.
Job Responsibility:
Gain deep technical knowledge across the Cloudera Data Engineering Experience stack, with a strong focus on Spark, and apply this expertise in your daily work
Build new features and improve Spark scale and performance to deliver a seamless experience for Cloudera’s data engineering customers
Work with a team of talented Spark and infrastructure engineers. Help hire and mentor engineers while supporting their career growth
Drive architecture and design discussions, providing strong technical direction for the team
Collaborate with product, engineering, and cross-functional partners, leading the delivery of several large, critical features in Cloudera’s Spark space
Work on large-scale distributed systems, ranging from hundreds to thousands of nodes in production clusters
Bring passion for programming, clean coding practices, attention to detail, and a strong focus on quality
Requirements:
BE, MS, or Ph.D. in Computer Science or equivalent experience
8+ years of experience as a software engineer building infrastructure systems
Experience developing Apache Spark or related technologies
Experience as a technical lead, from proposing new features to coordinating work across team members through product delivery
Ability to drive architecture and design discussions and provide technical direction
Strong understanding of at least one of the following languages: Java, Scala, Rust, C++, or Python
Excellent collaboration and communication skills
Nice to have:
Experience with one of the public clouds (AWS, Azure, GCP) and/or private cloud platforms (OpenShift, Rancher)
Experience with concurrent and distributed systems, especially on the JVM
Experience building and maintaining containerized applications on Kubernetes