Principal Engineer, Data

Principal Engineer, Data & AI Platforms Latinx in AI (LXAI) – Canada – Remote friendly (Canada, ON, Toronto) 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. 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 The Enterprise Data and AI Technologies & Architecture (EDATA) organization is a dynamic and evolving team that is spearheading Workday’s growth through trusted data excellence, innovation, and architectural thought leadership. Equipped with an array of skills in data & AI platforms and architecture, data science, engineering, machine learning and AI strategy & product management, this team orchestrates the flow of data across our growing company while ensuring data accessibility, accuracy, and security. With a relentless focus on innovation and efficiency, Workmates in EDATA enable the transformation of complex data sets into actionable insights that fuel strategic decisions and position Workday at the forefront of the technology industry. About The Role We are seeking a highly skilled and experienced Principal Engineer, Data and AI Platforms to lead our engineering efforts and drive the evolution of our Data and AI platform. The ideal candidate will possess a strong background in designing, building, and managing large‑scale Data and AI systems, with a focus on automation, scalability, and reliability. Data Leadership Define and champion the vision for a modern, scalable, and secure data platform, incorporating cloud‑native technologies and driving adoption of best practices in data modeling, data warehousing, and data lake architecture. Champion effective Data Platform principles and practices, ensuring automated data pipelines, CI/CD, and robust monitoring for efficient operations. Optimize data ingestion, transformation, and serving layers. Design and implement scalable Data and ML/AI platforms to accelerate the development, deployment, and management of ML/AI solutions in production. Ensure the data infrastructure supports the full ML/AI lifecycle. Optimize data infrastructure, applying concepts such as FinOps, Infrastructure as Code (IaC) for data and ML/AI infrastructure, promoting automation and CI/CD. Lead the governance of data architecture. Lead cross‑functional collaboration between data scientists, platform engineers, data engineers, operations, security and business teams to ensure alignment and effective data delivery. Keep abreast of the latest data and AI technologies, proactively identifying and evaluating new tools and methodologies to improve efficiency and performance of the data platform. Robust Development Lifecycle For Data Platforms Partner with engineering and product development teams to understand their needs and translate requirements into the relevant data and ML/AI workflows. Lead the selection, integration, and optimization of DevOps tools and technologies specific to data and ML/AI, including: CI/CD platforms (e.g., Jenkins, GitLab CI/CD) with integrations for data and ML/AI workflows. Infrastructure as Code (IaC) tools (e.g., Terraform) for provisioning and handling data and ML/AI infrastructure. Containerization technologies (e.g., Docker, Kubernetes) for deploying and scaling data and ML/AI applications. Architectural Standards & Best Practices Establish and enforce architectural standards, guidelines, best practices, and frameworks specific to data workloads, ensuring consistency and quality across all projects and systems. Promote a culture of automation, continuous integration, continuous delivery, and robust path to production across our data platforms. Drive the implementation of DataOps and MLOps methodologies. Collaboration & Communication Foster a culture of collaboration and shared responsibility between data scientists, platform engineers, data engineers, operations, and security teams, promoting effective communication and knowledge sharing. Effectively communicate technical concepts and solutions to both technical and non‑technical audiences, including business stakeholders and senior management. Innovation & Continuous Improvement Stay up‑to‑date with the latest DevOps trends and technologies relevant to data and ML/AI, proactively proposing, evaluating and designing proof‑of‑concepts on new tools and methodologies to improve efficiency and performance. Drive continuous improvement initiatives to optimize DataOps and MLOps processes, enhance automation, and reduce technical debt within the data platforms. Mentor and coach other engineers on architectural and engineering best practices specific to data and AI workloads. About You We’re looking for a seasoned professional who has driven large‑scale, complex data and AI solutions and can lead technical strategy, design, and delivery across a high‑performing team. Basic Qualifications 8+ years of hands‑on experience in Data Engineering, DataOps, MLOps, cloud architecture, DevOps, or related field. 8+ years of experience delivering large‑scale enterprise data and ML/AI solutions. 5+ years of experience with CI/CD pipelines, IaC tools, configuration management tools, containerization technologies, and infrastructure automation, with a focus on data and ML/AI workloads. 5+ years of experience with at least one major cloud platform (e.g., AWS, Azure, GCP) and its suite of products, including data and ML/AI services. 4+ years of experience with data platforms like Snowflake, Databricks, or similar technologies. Other Qualifications Proven ability to establish standard processes and lead multi‑functional teams, particularly within data and AI domains. Strong understanding of data management principles, data governance, and data security standard methodologies. Strong understanding of software development lifecycles and project delivery methodologies (Agile, Waterfall, etc.). Experience working collaboratively with third‑party vendors, as well as data scientists, ML engineers, software engineers, product development, and cloud operations teams. Excellent communication, interpersonal, and leadership skills with the ability to influence and mentor others. Strong problem‑solving and troubleshooting skills in technical environments. Ability to work in a fast‑paced, multi‑functional team environment. Bachelor’s degree in Computer Science, Engineering, Business, or a related field. 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). Those in our remote “home office” roles also have the opportunity to come together in our offices for important moments that matter. 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 CAN Base Pay Range $141,100 – $211,700 CAD Seniority Level Mid‑Senior level Employment Type Full‑time Job Function Engineering and Information Technology Industries Research Services EEO Statements Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Referral Note Referrals increase your chances of interviewing at Latinx in AI (LXAI) by 2x. Security and Privacy Notice 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. #J-18808-Ljbffr