Software Development Engineer; Distributed Systems

Software Development Engineer

Your work days are brighter here.

We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you'll feel it. Not just in the products we build, but in how we show up for each other.

Our culture is rooted in integrity, empathy, and shared enthusiasm. We're in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you'll do meaningful work with Workmates who've got your back.

In return, we'll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you've found a match in Workday, and we hope to be a match for you too.

The Data Platform and Observability Engineering (DPOE) team is building Workday's next-generation, multi-petabyte scale Observability Platform. We own the libraries, distributed services, and infrastructure that power ingestion, storage, and query across the observability stack — Iceberg, Click House, Tempo, Grafana, S3, Kafka, and Elasticsearch — serving traces, metrics, and logs for every workload  roadmap directly shapes how the company detects, diagnoses, and eventually predicts operational issues at scale.

As a Software Development Engineer, you will build and scale core features of Workday's distributed tracing platform. Working with Click House, Grafana Tempo, and a modern big-data pipeline (Kafka, Spark/Flink, Iceberg, S3) on AWS, you will deliver high-quality, high-performance code capable of handling massive data loads.

This is a hands-on role for an engineer who excels at building resilient backend services and is eager to grow their expertise in distributed systems and big data while contributing to the future of Observability AI.

• Develop the Platform:
  Write high-quality, well-tested code to build and scale features for the distributed tracing platform on Click House/Tempo, focusing on robust ingestion and fast query execution.
• Maintain Big-Data Pipelines:
  Build and support high-throughput data pipelines using Kafka, Spark/Flink, and Iceberg-on-S3.
• Tune and Optimize:
  Write optimized code and participate in profiling and resolving latency or throughput issues in production environments.
• Ensure Reliability:
  Implement robust error handling, retries, and failover mechanisms to ensure high availability for tracing services.
• Secure the Data:
  Apply necessary security controls to ensure multi-tenant data access is properly handled according to platform architecture.
• Operational Support:
  Maintain the health of the platform through comprehensive monitoring, logging, and alerting, and participate in the team's on-call rotation.
• Support Observability AI:
  Build reliable data ingestion paths that will serve as the foundation for AI-driven anomaly detection and root-cause analysis.
• Collaborate and Learn:
  Write clear technical documentation, participate actively in system design reviews, and work closely with Senior and Principal engineers to level up your distributed systems knowledge.

Basic Qualification

5+ years experience in software development engineering.
3+ years experience specifically focused on designing, building, and operating complex distributed system architectures, evidenced by successful deployment of systems with high availability (e.g., 99.9% uptime) and fault tolerance.
5+ years experience with at least two of the following programming languages Java, Python, Go, including experience in writing production-level code for distributed systems.

Bachelor's degree in a relevant field such as Computer Science, Engineering, or a related discipline; a Master's degree (e.g., MS in Computer Science, Distributed…