Principal Distributed Systems Engineer - Observability
Full time · Posted 12D AGO
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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 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 — including LangSmith for LLM/agentic tracing and evaluation 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 Role
To own the technical vision and architecture for distributed tracing as a first-class pillar of Workday's Observability Platform, built on ClickHouse and/or Grafana Tempo, backed by a big-data pipeline (Kafka, Spark/Flink, Iceberg, Clickhouse, Tempo,S3) running on AWS. This is a hands-on, high-autonomy role for an engineer who can design and build multi-petabyte, low-latency tracing infrastructure end-to-end — and who is equally excited to help define where Observability AI goes next: using traces, logs, and metrics as the substrate for automated root-cause analysis, anomaly detection, and AI-driven incident triage.
You'll set technical direction across multiple teams, mentor senior and staff engineers, and act as the primary architect and escalation point for the tracing subsystem — from ingestion and storage design through query performance and platform reliability.
- Architect and build Workday's distributed tracing platform on ClickHouse/Tempo, designed for multi-petabyte scale ingestion and sub-second interactive query performance.
- Own the big-data pipeline feeding tracing data — Kafka-based ingestion, Spark/Flink stream and batch processing, and Iceberg-on-S3 storage — including schema design, partitioning, compaction, and lifecycle management.
- Drive performance and scaling across ingestion and query paths: storage format optimization (Parquet/Iceberg), compression strategy, partitioning/indexing, and query engine tuning under real production load.
- Lead HA/DR design for tracing services — multi-region/multi-AZ resilience, failover, backup/restore, and recovery time/point objectives appropriate to a tier-1 platform.
- Design security architecture for the platform, including authentication/authorization (authn/authz) for multi-tenant data access across ingestion and query layers.
- Own operational excellence for distributed tracing: monitoring, logging, alerting, capacity planning, and participation in an on-call rotation for the platform.
- Evaluate and introduce new technologies — open source and cloud-native — that materially improve the platform's scalability, cost efficiency, or capability.
- Shape the future of Observability AI: Extend distributed tracing to LLM and agentic workflows using LangSmith and LangChain, enabling observability into multi-step agent execution, tool calls, and prompt/response chains.
- Evangelize the platform: publish best practices, mentor engineers across DPOE and partner teams, and act as a technical thought leader for the modern observability/data stack internally.
- Operate with high autonomy in a fast-moving, ambiguous environment — setting technical direction with minimal oversight while aligning with broader platform strategy.
About You
Basic Qualification
14+ years experience in software development engineering.
6+ 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.
8+ years experience with at least two of the following programming languages (e.g., 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
Expert-level ability in Algorithmic Thinking to architect highly efficient and scalable solutions for complex
Deep expertise in API Development, including understanding of advanced API protocols or architectural patterns
Deep understanding of Distributed Systems Software principles, like distributed consensus or fault tolerance mechanisms
Proven ability to design and implement High Availability strategies for critical distributed systems
Experience with LLM observability and tracing tools such as LangSmith, and familiarity with LangChain or similar agent orchestration frameworks
Extensive experience with Large Scale Data Processing technologies and frameworks
Deep understanding of Large Scale Systems design principles like distributed data management or scalability strategies
Strong understanding of System Security principles and best practices relevant to securing complex distributed environments
Proven ability to lead Team Collaboration within and across distributed software development teams and drive architectural direction
Strong skills in creating Technical Writing Documentation and Presentation
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 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
Our Approach to Flexible Work
With 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.
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