Job Software Developer/ Engineer/ Architect

Sr Software Development Engineer - Scalability Engineer

About the Team

Workday's Analytics Scalability organisation ensure our analytics platform including Workday Prism Analytics, core analytics and data services can scale to meet the needs of the world’s largest companies. The analytics platform spans data acquisition, data preparation, data discovery, business intelligence, and augmented analytics/machine learning and uses many open-source technologies like Hadoop, Spark and Yarn to handle significant amounts of data using distributed systems and fault-tolerant architecture.


About the Role

We are looking for an outstanding Software Development Engineer to join our Analytics Scalability Engineering team. The team have a deep technical understanding of software, distributed systems, cloud computing, cloud technologies, deployment, hardware, networking, and the Internet. Scalability Engineers are highly skilled engineers who debug, measure, analyze, and improve our Workday Analytics applications and infrastructure by working closely with all our engineering teams throughout the release cycle with a goal of ​revising architecture designs that provide real scalability, low latency, and high availability. The team also work on blocking issues, driving technical conversations among diverse teams.

Basic Qualifications:

  • Experience in building High Availability, multi-tenanted analytic applications in a Cloud environment
  • Experience with Data Processing frameworks like Hadoop and Spark
  • Experience with Performance, Load, Stress, and Scalability Testing
  • Ability to communicate cross functionally, partnering with Implementers, Engineers and Customer support
  • Understanding of Workload management techniques
  • Understanding of resource management using YARN, Kubernetes, etc.
  • Excellent coding skills, Java and Linux expertise
  • SQL skills or equivalent experience
  • Experience building applications or cloud related technologies


Additional Qualifications:

  • Knowledge of distributed system techniques
  • Experience with Apache Spark
  • Data Science: jupyter notebooks, python, pandas