About the TeamThe 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, ClickHouse, Tempo, Grafana, S3, Kafka, and Elasticsearch - serving traces, metrics, and logs for every workload at Workday. Our roadmap directly shapes how the company detects, diagnoses, and eventually predicts operational issues at scale.
About the RoleAs 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.
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.
Responsibilities- Develop the Platform: Write high-quality, well-tested code to build and scale features for the distributed tracing platform on ClickHouse/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.
About YouBasic 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 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: $148,000 USD - $222,000 USD
Additional US Location(s) Base Pay Range: $123,900 USD - $222,000 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.
