Senior Software Engineer - Data Platform (Spark & Trino)
About The Position
As part of Workday’s Data platform team, you will be responsible for building, enhancing, and extending our Spark and Trino-based large-scale distributed data processing platform in the cloud. You will work alongside a top-notch team to architect and build features representing our: High-velocity hybrid transactional/analytical engine Low-latency interactive engine Large scale cube builder engine. In this role, you will be a key driver in ensuring the platform is hardened for production at massive scale. This includes designing fault-tolerant architectures, building robust self-healing mechanisms, and implementing comprehensive telemetry to make the internal state of our distributed query engines completely transparent.
Requirements
- 8+ years of software development experience in Java and/or Scala in Linux/Unix environment.
- Experience operating large-scale distributed systems natively within public cloud environments (AWS or GCP)
- 3+ years in database internals, query processing, or distributed systems
- A strong grasp of SQL and distributed data processing engines (e.g., Apache Spark).
- Hands-on experience with Trino (formerly PrestoSQL) or Presto for executing fast, distributed SQL queries across large, heterogeneous data sources.
- Proven experience architecting and tuning distributed systems for high availability, fault tolerance, and massive horizontal scale.
- Experience implementing observability and telemetry frameworks (e.g., Prometheus, Grafana, OpenTelemetry, JMX metrics) to monitor complex distributed workloads.
- Industry experience building and delivering high-performance data processing engines.
Nice To Haves
- You have a BS in Computer Science or a related field with 5 years of experience, or an MS/PhD in Computer Science, or a relevant area, with 3 years of experience.
- Familiarity with AI coding tools like Cursor etc
- Experience leading or mentoring a team of engineers.
Responsibilities
- Developing data processing algorithms and techniques that work on large datasets, facilitating an interactive querying experience over large volumes of data.
- Resiliency: Designing and implementing strategies for high availability, fault isolation, and graceful degradation of Spark and Trino clusters.
- Observability: Building end-to-end tracing, deep metrics, and advanced alerting frameworks to proactively identify performance bottlenecks and system anomalies.
- Scalability: Optimizing resource allocation, cluster auto-scaling, and multi-tenant isolation to support highly elastic and unpredictable workloads.
Benefits
- Workday Bonus Plan or a role-specific commission/bonus
- Annual refresh stock grants
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What This Job Offers
Job Type
Full-time
Career Level
Senior
