Director, Data & AI Platforms and DevOps

Your work days are brighter here.

At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.

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About the Team

The Enterprise Data Services (EDS) 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 science, engineering, and analytics, 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 EDS enable the transformation of complex data sets into actionable insights that fuel strategic decisions and position Workday at the forefront of the technology industry. EDS is a global team distributed across the U.S., Canada and India.

About the Role

We are searching for a visionary and experienced Director to spearhead the strategy, development, and operation of our data ecosystem. You will be a transformative leader, responsible for building and scaling a world-class data and AI infrastructure that empowers data-driven decision making across all departments. You will lead a talented team of engineers, architects, and system administrators, fostering a culture of collaboration, innovation, and continuous improvement.

This role demands a deep understanding of Cloud Engineering, Data Engineering, AI/ML operations, Generative AI, Data Management, and enterprise reporting, coupled with strong leadership and communication skills. You will be a champion for data modernization, leveraging cutting-edge technologies and methodologies like cloud computing, data mesh, and serverless architecture. You will also be a key driver in integrating DevSecOps and Site Reliability Engineering principles into our data platforms, ensuring the security, reliability, and scalability of our data platform.

Key Responsibilities:

Strategic Leadership & Vision:

• Develop and execute a comprehensive data and AI platform strategy aligned with business objectives and industry best practices.

• Define the roadmap for data platform modernization, incorporating cloud-native technologies, microservices architecture, and data mesh concepts.

• Champion the adoption of new technologies and methodologies to improve platform efficiency, performance, and capabilities.

• Stay abreast of the latest trends and advancements in Data Engineering, AI/ML, and data platform technologies, including DevSecOps, SRE, GenAI and data platform modernization.

• Communicate the vision and strategy for the data and AI platform to stakeholders across the organization, including senior leadership.

Team Management & Development:

• Build, lead, and mentor a high-performing team of engineers, architects, and administrators.

• Foster a culture of collaboration, innovation, continuous learning, and knowledge sharing within the team.

• Conduct performance reviews, provide constructive feedback, and identify development opportunities for team members.

Data Architecture & Engineering:

• Oversee the design, implementation, and maintenance of a robust, secure, and scalable data infrastructure, including integration platforms, to ensure seamless data flow across the organization.

• Architect and implement data solutions, including data warehouses, data lakes, data pipelines, and data APIs, with a focus on scalability and performance.

• Ensure the optimal performance, availability, and scalability of the data platform, collaborating with IT infrastructure teams to leverage cloud services and advanced technologies.

• Implement and maintain data security protocols, collaborating with data governance teams and addressing any gaps.

MLOps & GenAI:

• Lead the implementation and optimization and efficient deployment, monitoring, and maintenance of AI/ML and GenAI platforms in production environments.

• Integrate GenAI platforms to deliver AI-powered insights and advanced analytics capabilities, driving innovation across business operations, particularly in R&D and Commercial functions.

• Collaborate closely with IT and Data Analytics teams to ensure that platforms effectively support their use cases while adhering to established standards.

Enterprise Reporting & Analytics:

• Manage the modernization and deployment of enterprise reporting platforms that provide real-time business intelligence and data visualization.

• Ensure these platforms are designed to support business stakeholders in monitoring performance, identifying risks, and making data-driven decisions, all supported by robust data engineering practices.

• Drive the adoption of these platforms and provide training and support to business users.

DevSecOps

• Integrate security practices throughout the data lifecycle, including infrastructure as code, automated security testing, and vulnerability management.

• Implement SRE principles like monitoring, alerting, incident management, and automation to ensure high availability and reliability of data and AI platforms.

• Define and track key performance indicators (KPIs) for the data platform, including availability, performance, security, and cost.

• Drive continuous improvement initiatives to enhance the efficiency and effectiveness of data operations.

Cross-Functional Collaboration & Communication:

• Partner with business leaders, product managers, and engineering teams across different departments to understand data requirements and provide data-driven insights.

• Effectively communicate technical concepts to both technical and non-technical audiences, including senior management.

• Present data platform updates, roadmaps, and performance metrics to stakeholders and senior leadership.

Vendor Management & Operational Efficiency:

• Manage relationships with external vendors to ensure they meet internal security, compliance, and performance expectations.

• Lead efforts in demand management, resource planning, and functional outsourcing to deliver high-quality data engineering and integration solutions efficiently and within budget.

• Drive continuous improvement in operational processes, ensuring alignment with business priorities while managing technical debt.

About You

Basic Qualifications:

• 15+ years of experience in data engineering or data warehousing.

• 8+ years in a senior leadership role managing teams

• 8+ years leading and inspiring large, diverse teams.

• Strong understanding of data architecture principles, data modeling techniques, and data integration patterns.

• Proficiency in data warehousing technologies (e.g., Snowflake, Redshift), data lake solutions (e.g., Databricks, AWS EMR), and ETL/ELT tools (e.g., Fivetran, dbt).

• Hands-on experience with cloud platforms like AWS, Azure, or GCP, and their data services.

• Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).

• Strong understanding of AI/ML concepts and experience with MLOps platforms and tools.

• Familiarity with GenAI technologies and their potential applications in business.

• Knowledge of data governance frameworks, data security best practices, and compliance regulations.

• Familiarity with integrating security practices throughout the data lifecycle, including infrastructure as code, automated security testing, and vulnerability management.

• Experience with implementing SRE principles like monitoring, alerting, incident management, and automation to ensure high availability and reliability of data platforms.

• Extensive experience with modernizing legacy data platforms by leveraging cloud-native technologies, microservices architecture, and data mesh concepts.

Other Qualifications:

• Strong Communication & Collaboration Skills, exceptional ability to effectively communicate technical concepts to both technical and non-technical audiences, build consensus, and influence stakeholders at all levels.

• Excellent Problem-Solving & Analytical Skills, proven ability to identify and solve complex data challenges, analyze data patterns, and drive data-driven decision-making.

• Strategic Thinking & Business Acumen, ability to align data and AI initiatives with broader business goals and demonstrate the value of data-driven decision-making.

• Open to 50% flex-hybrid reporting to our Toronto office

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 click here.

Primary Location: CAN.ON.Toronto

Primary CAN Base Pay Range: $151,800 - $227,800 CAD

Additional CAN Location(s) Base Pay Range: $151,800 - $227,800 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.

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