Sr Software Development Engineer - Distributed Systems

Workday Workday · Enterprise · Pleasanton, CA

Workday is seeking a Sr Software Development Engineer to join their OMS Data Lake team, which is a critical component of the Workday Data Cloud platform. The role involves architecting, building, and delivering platform capabilities and services for an Apache Iceberg zero-copy data lake solution. The engineer will focus on unifying real-time and analytical data from Workday's core operational business applications, building robust, high-performance services that expose transactional application engine data as optimized Iceberg tables with strict consistency and advanced metadata management. The role requires deep experience in Software Engineering, Big Data Platform Architecture, and Distributed Systems, with proficiency in Java, Apache Iceberg, Apache Spark, and multi-cloud infrastructure (AWS, GCP).

What you'd actually do

  1. architecting, building, and delivering the platform capabilities and services that power our Apache Iceberg zero-copy data lake solution
  2. unlocking and unifying real-time and analytical data from Workday’s core operational business applications—including Human Capital Management (HCM), Financial Management, Recruiting, and more—without costly data duplication or heavy ETL overhead
  3. building robust, high-performance services that expose transactional application engine data as optimized Iceberg tables, ensuring strict consistency, advanced metadata management, schema evolution, and multi-cloud data accessibility for both internal analytical engines and external third-party consumers
  4. Deploying, tuning, and maintaining data services within cloud-managed ecosystems across AWS and GCP
  5. production resiliency, monitoring, and debugging massive data platform infrastructure

Skills

Required

  • Java
  • Scala
  • Python
  • Apache Iceberg
  • Apache Spark
  • Large-scale Database Internals (Relational, NoSQL, and Columnar Engine Concepts)
  • Distributed Processing
  • Query Execution/Optimization
  • Storage-Compute Separation
  • High-Throughput Service Mesh
  • Multi-Cloud Managed Services: Amazon Web Services (AWS) & Google Cloud Platform (GCP)
  • Software Engineering
  • Big Data Platform Architecture
  • Distributed Systems
  • highly concurrent software
  • Apache Trino
  • Parquet
  • database technologies
  • transaction processing (ACID properties)
  • query execution plans
  • file formats
  • operating system concepts
  • memory and storage management
  • threading
  • concurrency control
  • networking
  • object-oriented software
  • clean code principles
  • API design
  • production resiliency
  • monitoring
  • debugging massive data platform infrastructure

Nice to have

  • BSc, MSc, or PhD in Computer Science, Computer Engineering, or an equivalent technical field
  • Grafana
  • Prometheus
  • Kibana

What the JD emphasized

  • 8+ years of deep experience in Software Engineering, Big Data Platform Architecture, Distributed Systems, or a related technical field
  • 5+ years of production-level experience designing and implementing highly concurrent software using Java
  • Proven expertise with large-scale data processing frameworks like Apache Spark or Trino, and modern open table formats such as Apache Iceberg and Parquet
  • Strong working knowledge of deploying, tuning, and maintaining data services within cloud-managed ecosystems across AWS and GCP