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Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. About the Team Datahub is an AI/MLOps centered Data engineering team and our goal is to ingest, compute, and surface data driving key Workday applications across the company. About the Role In this role, you will contribute to a cloud ops platform that enables ingestion of data from internal and external producers, computes and aggregate meaningful, curated data sets, the surfaces these sets to Workday Front-End components or as embedded contextual data for AI/ML inference generation and agentic workflows. We utilize technologies like Kubernetes, Spark, Python, Java, XO, Terraform, Kubernetes, Iceberg, EMR, and Sagemaker. About You Basic Qualifications (Senior Software Engineer): 6+ years of experience in Software Engineering, Distributed Systems or a related field 3+ years proficiency in at least two of the following programming languages: Java, Scala, Python 3+ years in cloud 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, Kubernetes, Terraform AWS Cloud Infrastructure Basic Qualifications (Software Engineer): 3+ years of experience in Software Engineering, Distributed Systems or a related field 3+ years proficiency in at least two of the following programming languages: Java, Scala, Python 3+ years in cloud 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, Kubernetes, Terraform AWS Cloud Infrastructure Other Qualifications: BSc or MSc in Computer Science/Computer Engineering or equivalent experience Experience in delivering a service from writing code to deploying in production: continuous integration (Jenkins), virtualisation (Docker), orchestration (Kubernetes, Terraform) Experience utilizing AI-Code Generation tools such as ClaudeCode, Windsurf, Cursor etc 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 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 click here. Primary Location: CAN.ON.Toronto Primary Location Base Pay Range: $140,000 CAD - $210,000 CAD Primary CAN Base Pay Range: $112,000 - $168,000 CAD Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email accommodations@workday.com. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not. In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

What you’ll do

You will contribute to a cloud ops platform that ingests, computes, and surfaces data for Workday applications and AI/ML workflows. This involves managing data pipelines and ensuring the scalability and reliability of service endpoints.

Requirements

Candidates must have 3-6+ years of experience in software engineering or distributed systems with proficiency in Java, Scala, or Python. Strong knowledge of cloud infrastructure and data engineering technologies like Spark, Iceberg, or Kubernetes is required.

Benefits

• Bonus plan • Stock grants • Flexible work

Listed skills

• Kubernetes · Preferred
• CI/CD · Preferred
• Docker · Preferred
• Amazon Web Services · Preferred
• Java · Preferred
• Terraform · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Java
• Scala
• Python
• Kubernetes
• Apache Spark
• Apache Iceberg
• Terraform
• AWS
• Cloud engineering
• Distributed systems
• Data engineering
• CI/CD
• Docker
• Monitoring
• Object-oriented programming
• Performance tuning
• Claude Code
• Courage
• Empathy
• AWS SageMaker
• DataHub (Software)
• Optimism
• MLOps (Machine Learning Operations)
• People Management
• Workflow Management
• Sales Prospecting
• Curiosity
• Cloud Operations
• Programming Languages
• Java (Programming Language)
• Apache Flex
• Artificial Intelligence
• Amazon Web Services
• Software Development
• Network Sockets
• Cloud Engineering
• Cloud Infrastructure
• Code Generation
• Computer Science
• Computer Engineering
• Consulting
• Continuous Integration
• Data Engineering
• Data Security
• Operating Systems
• Apache Hive
• Scalability
• Python (Programming Language)
• Machine Learning
• Managed Services

Job areas

• Software
• Data & Analytics
• Technology
• Engineering
• Data Software Engineer
• Software Developer / Engineer
• Software Developers