Data Quality Engineer

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

In 2024, Workday launched an Enterprise Data and Analytics team with a mission to transform and optimize the way Workday creates and shares trusted data to drive actionable insights and data led innovation across the enterprise. The team has introduced a new, cloud based technical stack, a Data Product methodology anchored in the principles of Data Ops, an Active Data Governance methodology to manage the quality and discovery of data, and a series of modern analytics tools that facilitate discovery, analysis, visualization, machine learning, and AI. The team’s goal is to lead high value cross-functional data and analytics work and to establish and support the broader Workday analytics community by establishing modern, common ways of working, facilitating training and communication, and creating secure data and analytics brokering capability across business units.

About the Role

Data Profiling and Analysis:

• Conduct thorough data profiling to understand data patterns, identify anomalies, and assess data quality.

• Analyze data to identify root causes of data quality issues and propose solutions.

Data Quality Rule Development and Implementation:

• Develop and implement data quality rules, checks, and validations using SQL and other relevant tools.

• Design and implement automated data quality monitoring and alerting systems.

Data Quality Tooling and Automation:

• Evaluate and implement data quality tools and technologies.

• Automate data quality processes to improve efficiency and scalability.

Collaboration and Communication:

• Collaborate with data engineers, data scientists, and business stakeholders to understand data requirements and address data quality concerns.

• Communicate data quality findings and recommendations effectively to technical and non-technical audiences.

• Document all data quality processes, rules, and findings.

Issue Resolution and Remediation:

• Troubleshoot and resolve data quality issues in a timely and efficient manner.

• Develop and implement data remediation strategies.

About You

The person in this role should have a good understanding of the data engineering domain with a proven track record of building and supporting data and analytics engineering solutions using modern data engineering tools and technologies.

Basic Qualifications:

• 3+ years of experience in data quality engineering or a similar role.

• Strong proficiency in SQL for data querying and manipulation.

• Experience with data profiling and data quality assessment tools.

• Familiarity with data warehousing (Snowflake) and ETL/ELT processes.

• Understanding of data governance principles and best practices.

• Experience with scripting languages (e.g., Python) for data automation is a plus.

• Excellent analytical and problem-solving skills.

• Strong communication and collaboration skills.

• Experience with version control systems like Git.

Preferred Qualifications:

• Knowledge of data modelling and database design.

• Experience with cloud based data warehousing tools like Snowflake.

• Experience with data transformation tools like dbt.

• Experience with data observability tools like Acceldata.

• Experience with CI/CD pipelines.

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.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!