Software Development Engineer(Distributed Systems)

Role details

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. About the Team The Data Platform and Observability Engineering (DPOE) team is building Workday’s next-generation, multi-petabyte-scale Observability Platform. We are a distributed team responsible for the libraries, distributed services, and infrastructure that power observability across Workday. Our stack includes Iceberg, ClickHouse, Tempo, Grafana, S3, Kafka, Elasticsearch, and LangSmith for LLM/agentic tracing and evaluation. Together, we support traces, metrics, logs, and LLM/agent observability across Workday workloads at scale. About the Role As a Software Development Engineer, you will build and scale core features of Workday’s distributed tracing platform. Working with ClickHouse, 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.You will optimize low-latency infrastructure and help shape the future of Observability AI by extending distributed tracing to LLM and agentic workflows using LangSmith and LangChain, enabling visibility into agent execution, tool calls, and prompt/response chains. 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. About You 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 Systems, or related field) is strongly preferred or equivalent practical experience. Other Qualification Strong ability in Algorithmic to build highly efficient and scalable solutions for complex high-throughput data ingestion and sub-second query performance challenges. Solid experience in API Development, including an understanding of gRPC, REST, and OpenTelemetry (OTLP), with practical experience designing and building scalable distributed APIs for observability data. Strong understanding of Code Testing methodologies, such as distributed load testing and integration testing, and experience contributing to end-to-end telemetry pipeline testing and CI/CD automation. Solid understanding of Distributed Systems Software principles, including data partitioning, eventual consistency, and fault tolerance mechanisms, with hands-on experience in Kafka, Spark, Flink, or ClickHouse. Experience implementing and maintaining High Availability strategies for critical distributed systems, including multi-AZ deployments, robust retry mechanisms, and automated failover. Practical experience with Large Scale Data Processing technologies and frameworks such as Apache Kafka, Spark, Flink, and Apache Iceberg within complex distributed architectures. Good understanding of Large Scale Systems design principles, including distributed data sharding, replication, and query optimization, and experience working on observability pipelines or data lake platforms. Strong understanding of Object-Oriented Design (OOD) principles and architectural patterns for building highly scalable and maintainable distributed systems. Experience with Source Control Management (SCM) tools such as Git and GitHub/Bitbucket, and following best practices for collaborative distributed development workflows. Strong understanding of System Security principles and best practices relevant to securing distributed environments, including mutual TLS (mTLS), multi-tenant authorization (authz), and data encryption. Proven ability to actively collaborate within and across distributed software development teams and contribute constructively to architectural discussions and system designs. Strong skills in creating Technical Writing Documentation for runbooks, system design specs, and API documentation related to distributed systems architecture and design. Workday Pay Transparency Statement The 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 mu