Senior Software Engineer (Data Engineering)

Workday•Vancouver, BC

1d•CA$140,000 - CA$210,000•Hybrid

About The Position

Workday is seeking a Senior Software Engineer specializing in Data Engineering to join their AI/ML-centered data engineering team, known as Platypus. This team is responsible for ingesting, managing, deriving, and serving data for Workday's AI/ML features. The role involves contributing to the ingestion, discoverability, governance, derivation, and serving of data for Workday's Classic Machine Learning and agentic initiatives. You will work hands-on with technologies such as Python, Spark, AWS Infra, Kafka, Terraform/Kubernetes, and Iceberg.

Requirements

BSc or MSc in Computer Science/Computer Engineering or equivalent experience.
7+ years of experience in Software Engineering, Distributed Systems, or a related field.
4+ years proficiency in at least two of the following programming languages: Java, Scala, Python.
4+ years in data engineering or related field(s).
Working knowledge of cloud-based infrastructure and managed services (AWS, GCP).
Experience with at least one of these data engineering technologies: Apache Spark, Apache Iceberg, Apache Avro, Apache Kafka, Apache Flink.
Experience in delivering a service from writing code to deploying in production: continuous integration (Jenkins), virtualization (Docker), orchestration (Kubernetes, Terraform).
Experience creating scalable service endpoints to retrieve data.
Track record of working with logging, monitoring, metrics, stats technologies, such as: Grafana, Prometheus, Kibana, Hive, etc.
Proficient collaborating with teammates to design, maintain and improve sophisticated object-oriented software following clean code standard methodology.
A testing/quality approach - unit, system/integration and end-to-end testing, TDD, feature toggles, and canary deployments.
Exposure to operating system concepts covering memory and storage, threading and concurrency, networking and sockets, and process management.
An understanding and experience with topics related to performance and scale, security, availability, deployment and operations.
Experience being responsible for a service in production with experience of 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 technologies like Python, Spark, AWS Infra, Kafka, Terraform/Kubernetes, and Iceberg.
Deliver a service from writing code to deploying in production, utilizing continuous integration (Jenkins), virtualization (Docker), and orchestration (Kubernetes, Terraform).
Create scalable service endpoints to retrieve data.
Work with logging, monitoring, metrics, and stats technologies such as Grafana, Prometheus, Kibana, Hive, etc.
Collaborate with teammates to design, maintain, and improve sophisticated object-oriented software following clean code standard methodology.
Employ a testing/quality approach including unit, system/integration, and end-to-end testing, TDD, feature toggles, and canary deployments.
Be responsible for a service in production, including production triage and on-call duties.