Principal Engineer of Data and AI Platforms, Workday
CA$141.1-211.7k
More information about location
Enterprise management cloud platform
Be an early applicant
Enterprise management cloud platform
1001+ employees
Be an early applicant
CA$141.1-211.7k
More information about location
1001+ employees
Company mission
To provide an all-in-one management cloud solution for the rapidly changing business requirements of the modern world.
Role
Who you are
- 8+ years of hands-on experience in Data Engineering, DataOps, MLOps, cloud architecture, DevOps, or related fields, with a consistent record of 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
- Bachelor’s degree in Computer Science, Engineering, Business, or a related field
- 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
What the job involves
- 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
- 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 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
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.
Workday has acquired and paired up with many other companies to keep expanding its offering. In 2021, it purchased the employee feedback platform Peakon in response to the growing need for managers to be able to survey workers and collect satisfaction data without face-to-face meetings. The company has also bought and developed many financial tools and HR management tools.
The company’s goal is to provide end-to-end back office services and while there are other providers, such as UKG Pro and Ceridian HCM, Workday’s broad offering helps them to stand out. Though it faced a tough global market in 2023 and has shed some of its headcount, Workday has seen a 6.5% gain in value in the first quarter of 2024. It is now focusing on growth and developing the AI capabilities of its platform. .
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 benefits
- Company equity
- Vision and dental insurance
- Work from home opportunities
- Health insurance
- Virtual primary care
- Flexible time-off policy
- Global mental health resources
- Global dedicated on-site clinical counselors
- Global well-being days
- $25k fertility/family planning benefits
- North Star financial wellness
- Retirement funds and matching
Company HQ
Pleasanton, CA
Leadership
Aneel Bhusri
(CEO)Worked for Morgan Stanley for 3 years and took a Stanford MBA, before spending almost 6 years at Oracle as SVP. Co-founded Workday in 2005 while working as a Greylock Advisory Partner.
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