Senior Software Engineer (Data Engineering)

Workday • Pleasanton, CA

1d • Hybrid

About The Position

Workday’s Platypus team is an AI/ML-centered data engineering team that ingests, manages, derives, and serves data across Workday’s growing suite of AI/ML features. In this role, you will contribute to data ingestion, discoverability, governance, derivation, and serving for Workday’s Classic Machine Learning and agentic initiatives. The work is hands-on with technologies including Python, Spark, AWS infrastructure, Kafka, Terraform/Kubernetes, and Iceberg.

The role is suited to a motivated software engineer with a passion for data engineering and machine learning who applies technology to Workday business initiatives. You will collaborate closely with colleagues to deliver solutions, communicate technical ideas effectively, and continue learning in distributed systems, data engineering, and machine learning.

Workday uses a flexible-work approach combining in-person and remote work. Teams spend at least 50% of their time each quarter in the office or in the field with customers, prospects, and partners, with schedules shaped around business, team, and personal needs. Remote home-office employees may also come together in offices for important occasions.

Requirements

• BSc or MSc in Computer Science/Computer Engineering, or equivalent experience.
• At least 7 years of experience in software engineering, distributed systems, or a related field.
• At least 4 years of proficiency in at least two of Java, Scala, and Python.
• At least 4 years in data engineering or related fields.
• Working knowledge of cloud-based infrastructure and managed services, such as AWS or GCP.
• Experience with at least one of Apache Spark, Apache Iceberg, Apache Avro, Apache Kafka, or Apache Flink.
• Experience delivering a service from code through production deployment, including continuous integration, virtualization, and orchestration technologies such as Jenkins, Docker, Kubernetes, and Terraform.
• Experience creating scalable service endpoints to retrieve data.
• Experience with logging, monitoring, metrics, or statistics technologies such as Grafana, Prometheus, Kibana, or Hive.
• Ability to collaborate with teammates to design, maintain, and improve sophisticated object-oriented software using clean-code practices.
• Experience with software testing and quality approaches, including unit, system/integration, and end-to-end testing, TDD, feature toggles, and canary deployments.
• Exposure to operating system concepts including memory and storage, threading and concurrency, networking and sockets, and process management.
• Understanding and experience with performance and scale, security, availability, deployment, and operations.
• Experience being responsible for a production service, including production triage and on-call.

Responsibilities

• Contribute to the ingestion, discoverability, governance, derivation, and serving of data for Workday’s Classic Machine Learning and agentic initiatives.
• Work hands-on with data engineering and infrastructure technologies, including Python, Spark, AWS infrastructure, Kafka, Terraform/Kubernetes, and Iceberg.
• Collaborate with colleagues to design, maintain, and improve sophisticated software.
• Deliver services from writing code through production deployment.
• Support services in production, including production triage and on-call responsibilities.

Benefits

• The role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus.
• Annual refresh stock grants may be included in the total compensation package.
• Workday describes its flexible-work approach as offering flexibility to shape schedules around business, team, and personal needs.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior