About the TeamThe Data Cloud organization is at the forefront of Workday's next major wave of innovation, driven by a bold mandate to build the industry's first true Platform for Agents. We are a high-energy, ambitious team that balances Workday's deep foundational expertise with fresh, forward-thinking perspectives to accelerate our pace of delivery and unlock massive new commercial value. By leveraging Workday's unique business context, trusted data, and identity guardrails, we are building the critical engine that will power the future of AI and agentic workflows across the enterprise.
About the RoleAs part of Workday's Data Platform Engineering org, you will be responsible for building and enhancing Workday's Data Cloud. You will work with a top-notch team to architect and build features in our distributed ingestion, transaction and query processing engines. You will be responsible for developing algorithms and techniques for supporting fast, efficient transactions and queries over large scale data, in a multi-tenanted cloud environment.
About YouYou are an engineer who takes pride in your work. Furthermore, you:- Understand the importance of doing what is right for the customer
- Are passionate about software development and think and code in terms of well-defined abstractions
- Enjoy coming up with novel solutions and can clearly articulate their value to stakeholders
- Are excited about working as part of an engineering team
- Have a strong interest in learning about and developing data management and distributed data processing systems and algorithms
- Are a fast learner who enjoys exploring new technical areas, languages, and frameworks
Basic Qualifications- 7+ years using any of the following programming languages: Java, Scala, C++, Go, or Rust
- 3+ years development experience in relevant domain areas (e.g. database internals, distributed system application, JVM performance tuning, Cloud/SaaS Services, etc.)
- Bachelor's degree in Computer Science or relevant field or MS in Computer Science or a relevant field
Other Qualifications- 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
- 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
Workday Pay Transparency StatementThe annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.
Primary Location: USA.CA.Pleasanton
Primary Location Base Pay Range: $190,100 USD - $285,100 USD
Additional US Location(s) Base Pay Range: $160,100 USD - $285,100 USD
Our Approach to Flexible WorkWith Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply
spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
