About the Role
In this role, you will contribute to the ingestion, discoverability, governance, derivation, and serving of data for Workday's Classic Machine Learning and agentic initiatives. You'll be working hands-on with technologies like Python, Spark, AWS Infra, Kafka, Terraform/Kubernetes, and Iceberg.
About You
You are a highly motivated and skilled Software engineer with a passion for data engineering and machine learning. You strive to apply technology to drive real impact on Workday's business initiatives. You thrive in a collaborative environment, working closely with your colleagues to deliver innovative solutions. You possess excellent communication skills, actively listening to understand different perspectives and effectively conveying technical ideas. You are eager to contribute to a high-performing team and are driven to continuously learn and grow in the ever-evolving world of Distributed Systems, Data Engineering, and Machine Learning.
Basic Qualifications: (Required)
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
Other Qualifications:
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.
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 .
Primary Location: CAN.BC.VancouverPrimary CAN Base Pay Range: $140,000 - $210,000 CADAdditional CAN Location(s) Base Pay Range: $140,000 - $210,000 CADSenior Software Engineer (Data Engineering) • Toronto, ON, Canada
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