Software Engineer, Data Cloud – Distributed Data Systems

Job Description

Senior Software Development Engineer – Data Cloud | Workday

The Tone:
This is a full-time role at Workday, located in Pleasanton, CA, with a hybrid work model. Workday is a Fortune 500 company and a leading AI platform for managing people, money, and agents, shaping the future of work. This role is crucial for building and enhancing Workday’s Data Cloud, which is at the forefront of the company’s next major wave of innovation to power the future of AI and agentic workflows across the enterprise.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: Hybrid – Pleasanton
• Pay: $160100–$285100 yearly
• Team: Data Platform Engineering org (Data Cloud organization)
• Mission: Responsible for building and enhancing Workday’s Data Cloud, focusing on distributed ingestion, transaction, and query processing engines.
• Tech Stack: Java, Scala, C++, Go, Rust, Kubernetes, Apache Spark, Spark SQL internals, Apache Iceberg, zero-copy architectures, Apache Polaris, Trino, MySql, PostgreSQL, DuckDB, JVM performance tuning

What You’ll Actually Do
• Architect: Architect and build features within distributed ingestion, transaction, and query processing engines.
• Develop: Develop algorithms and techniques for fast, efficient transactions and queries over large-scale data.
• Enhance: Enhance Workday’s Data Cloud in a multi-tenanted cloud environment.
• Contribute: Contribute to the engineering team by proposing and articulating novel solutions to stakeholders.
• Explore: Explore new technical areas, languages, and frameworks related to data management and distributed data processing.

The Must-Haves
• Background: Bachelor’s degree in Computer Science or relevant field or MS in Computer Science or a relevant field. This is a Senior-level role focused on data management and distributed data processing systems.
• Experience: 7+ years using Java, Scala, C++, Go, or Rust. 3+ years development experience in database internals, distributed system application, JVM performance tuning, or Cloud/SaaS Services.
• Skills: Background in data warehousing, database system internals and/or distributed systems. Expertise in distributed data processing engines or data management systems. A strong understanding of SQL.
• Bonus: Experience with one or more of: Kubernetes, Apache Spark and Spark SQL internals, Apache Iceberg and zero-copy architectures, Apache Polaris, Trino, MySql, PostgreSQL, DuckDB.