Data Platform Engineer – Data Cloud Engineering

Job Description

Software Development Engineer – Data Cloud | Workday

The Tone:
This is a full-time hybrid role at Workday, with a primary location in Pleasanton, CA. Workday builds a leading AI platform for managing people, money, and agents, shaping the future of work. This role is critical for building and enhancing the Workday Data Cloud, which will serve as the engine to power future AI and agentic workflows across the enterprise by processing large volumes of trusted data.

The TL;DR
• Role: Full Time
• Type: Full Time
• Location: Hybrid Pleasanton
• Pay: $148000–$222000 USD yearly
• Team: Data Cloud organization within Workday’s Data Platform Engineering org
• Mission: Build and enhance Workday’s Data Cloud by developing infrastructure for high-performance data crunching, data management, and distributed data processing.
• Tech Stack: Kubernetes, Apache Spark, Spark SQL internals, Apache Iceberg, zero-copy architectures, Apache Polaris, Trino, SQL

What You’ll Actually Do
• Build: Construct and enhance Workday’s Data Cloud components and systems.
• Develop: Create infrastructure that powers high-performance data crunching on large volumes of data.
• Ensure: Maintain simplicity and ease-of-use for the overall data product while prioritizing performance, scalability, and reliability.
• Articulate: Clearly communicate the value proposition of brilliant ideas to partners and stakeholders.
• Implement: Translate novel technical ideas into solid, high-quality implementations that drive customer success.

The Must-Haves
• Background: Bachelor’s degree in Computer Science or a relevant field, or an MS in Computer Science or a relevant field, coupled with a strong interest in learning about and developing data management and distributed data processing systems and algorithms.
• Experience: 4+ years of software development experience in an object-oriented or functional language, including a background in data warehousing, database system internals, and/or distributed systems, along with experience in distributed data processing engines or data management systems.
• Skills: Proficiency in an object-oriented or functional programming language, a good grasp of SQL, and the ability to design systems with constant consideration for performance, scalability, and reliability.
• Bonus: Experience with one or more of: Kubernetes, Apache Spark and Spark SQL internals, Apache Iceberg and zero-copy architectures, Apache Polaris, Trino.