Principal Engineer, Workday
Data & AI Platforms
CA$141.1-211.7k
More information about location
Enterprise AI platform for managing HR and finance
Be an early applicant
Enterprise AI platform for managing HR and finance
1001+ employees
Be an early applicant
CA$141.1-211.7k
More information about location
1001+ employees
Company mission
To leverage the power of AI to elevate humans and supercharge work, moving business forever forward.
Role
Who you are
- 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
- 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
- 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
What the job involves
- 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
- 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
- Data Leadership:
- Define and champion the vision for a modern, scalable, and secure data platform, incorporating cloud-native technologies and drive 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 a 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 methodologie
- 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
Our take
Workday is a cloud-based software vendor that provides management of workforces and finances. The company uses a single database for workforce management and financial management to offer integration and optimize business intelligence across companies. It has added to the packages and tools it offers over the years, providing analytic options that allow companies to combine third-party data with information collected by Workday.
The company has also grown through acquisitions and partnerships to broaden its capabilities.. Most recently, in 2025 it purchases Sana, an AI-driven enterprise knowledge and learning platform, to create a "new front door for work". This acquisition allows Workday to integrate Sana's AI-powered search, agents, and learning capabilities with its own data and workflows, allowing employees to access information, automate tasks, and complete their day entirely within Workday.
Through a combination of strategic acquisitions and in-house development, WOrkday has built a comprehensive suite of HR, financial, and enterprise tools. By focusing on innovation and AI-driven workflows, the company continues to push productivity and decision-making for organizations worldwide. Building on this track record, Workday is very much positioned for even more growth, reinforcing its status as a leader in shaping the future of work.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Oct 2011
$85m
SERIES F
Apr 2009
$75m
SERIES E
Total funding: $215.3m
Company HQ
Pleasanton, CA
Leadership
Aneel Bhusri
(Co-Founder & Executive Chair)Annel began his career at Morgan Stanley as a Corporate Finance Analyst. He then spent nearly 6 years at PeopleSoft as a Senior VP before co-founding Workday in 2005, where he has served as the CEO ever since.
Carl Eschenbach
(CEO)Carl joined Workday in 2022 as Co-CEO, becoming CEO in 2024. He has also been a Partner at Sequoia Capital since 2016. Previously, he spent 14 years at VMware as President and COO and 3 years at Inktomi Corporation as the VP of North America Sales.
Peter Bailis
(CTO)Prior to joining Workday in 2025, People was a VP of Engineering at Google. He also previously founded Sisu Data, where he served as the CEO for over 5 years.
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