Data Quality Engineer

About Workday

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, its 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.

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, India and Canada.

• Designing and implementing data quality checks, identifying, and resolving data quality issues, collaborating with data engineers and product team to improve data pipelines, and developing data quality standards and best practices.
• Collaborate with data engineers, analysts, and business stakeholders to understand data requirements and quality expectations.
• Analyze architecture and designs to identify test automation strategies to provide full test coverage for new and/or existing data quality checks. Identify and articulate gaps in architecture or design which would lead to data quality issues. Goal here is to validate, automate and maintain high-quality data that supports informed decision-making and business operations.
• Monitor and analyze data quality metrics to proactively identify issues and opportunities for improvement.
• Establish data quality monitoring processes as part of CI/CD and tools to ensure ongoing compliance with quality standards.
• Investigate root causes of data quality issues and work with relevant teams (upstream, downstream & Analyst) to implement corrective actions.
• Provide technical guidance and support to ensure data quality standards are integrated into all data-related projects and initiatives.
• Work closely with Data Operations & Support, Monitoring team to capture production data quality exceptions and mitigate business impact/risk
• Document data quality processes, procedures, and standards for reference and training purposes.

• Bachelors degree in Computer Science, Information Systems, or a related field; Masters degree preferred.
• Proven experience as a Data Quality Engineer or similar role, with a minimum of 5 years in data quality management or data governance.
• Solid understanding of data management concepts, including data profiling, data cleansing, and data integration.
• Proficiency in SQL for data querying and manipulation. Develop and execute automated data quality tests using tools like SQL, Python (Pyspark), and data quality frameworks.
• Experience with working in a cloud environment (AWS, GCP) preferred.
• Experience with data warehousing solutions (Snowflake, Databricks, Redshift) preferred.
• Experience with data integration and transformation tools (e.g. Snaplogic, Prophecy, dbt, Talend, etc.) a plus.
• Experience with data quality monitoring tools (Acceldata, Tricentis) a plus.
• Working knowledge of DevOps principles and CI/CD pipelines preferred.
• Strong analytical skills with the ability to identify patterns, trends, and outliers in data.
• Strong problem-solving skills and attention to detail.

• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
• Proven ability to prioritize and manage multiple tasks in a fast-paced environment.
• Certification in relevant technologies or data management disciplines is a plus.
• Analytical mindset with the ability to think strategically and make data-driven decisions.