Requisition ID: 44511

Job Description

In every role, McCainers are ambitious, curious, and passionate about creating exceptional work experiences - together. With a customer-first mindset, we make doing business with McCain easy.

About the role.

As part of McCain’s digital transformation, we are making significant investments in our data foundations, structures, and policies to improve data quality, strengthen confidence in business decision-making, and generate greater value from data.

The Principal Data Quality and Governance Engineer is responsible for helping ensure that enterprise data is accurate, trusted, secure, discoverable, and well governed. This role leads complex data profiling and quality assessments, operationalizes metadata management and cataloging capabilities, and implements effective access, classification, and data protection controls across enterprise data platforms.

Working closely with business data governance stakeholders, data engineering, architecture, analytics, and security teams, the Principal Data Quality and Governance Engineer enables consistent data practices, reduces data risk, and strengthens the organization’s ability to use data confidently for operations, reporting, analytics, and strategic decision-making.

What you’ll be doing.

• Establish and maintain enterprise data quality frameworks and standards covering data accuracy, completeness, consistency, timeliness, and validity.
• Lead data quality discovery workshops with business stakeholders and collaborate with data owners, stewards, and technical teams to define quality metrics, key performance indicators, validation processes, and remediation priorities.
• Perform data profiling, cleansing, validation, and ongoing monitoring using data quality tools, SQL, Python, and AI-enabled anomaly detection capabilities.
• Lead root-cause analysis and remediation activities for complex data quality issues, using data lineage and transformation details to identify upstream and downstream impacts.
• Document business rules, validation logic, exception-handling procedures, and quality controls for critical enterprise datasets.
• Maintain the enterprise data catalog, business and technical metadata, and end-to-end data lineage to reflect new data sources, system enhancements, business terminology, transformations, and architectural changes.
• Identify and document data transfers across business units, legal entities, systems, and third parties, partnering with data engineers, architects, and business teams to capture associated data flows and transformations.
• Implement tools and practices that standardize metadata capture, classification, tagging, lineage, and documentation, including AI-enabled auto-classification capabilities that improve data discoverability.
• Support the implementation and optimization of enterprise data governance, reference data, metadata management, data catalog, and data quality platforms, while driving adoption through training, onboarding, and documentation.
• Define and maintain enterprise data sensitivity taxonomies and a data protection control framework covering structured and unstructured data, including personal, health, financial, commercially sensitive, and trade-secret information.

What you’ll need to be successful.

• Bachelor’s degree in Management Information Systems, Engineering, Mathematics, Computer Science, Information Technology, or a related field.
• At least five years of experience in data governance, data quality, metadata management, or a related data discipline.
• Proven experience working in a large, matrixed, global organization with multiple business units and regional data environments.
• Strong understanding of data quality principles, metadata standards, data lineage, data classification, data cataloging, and data protection controls.
• Demonstrated ability to lead data quality discovery, root-cause analysis, issue remediation, and governance initiatives across cross-functional teams.
• Strong SQL or Python skills, with experience developing and optimizing queries or scripts for data profiling, validation, monitoring, and analysis.
• Hands-on experience with enterprise data governance and data management platforms such as Ataccama, Syniti, Collibra, Microsoft Purview, Informatica, or Alation.
• Experience supporting the implementation, configuration, rollout, and adoption of enterprise data governance, cataloging, reference data, or data quality platforms.
• Experience with modern cloud data platforms and technologies such as Databricks, Snowflake, or AWS.
• Ability to establish meaningful metrics and key performance indicators that measure data quality, governance adoption, business impact, catalog coverage, and process compliance.
• Strong stakeholder-management and communication skills, with experience working with data owners, data stewards, IT teams, business functions, and senior leaders.
• Ability to operate independently, manage competing priorities, and deliver results in a fast-paced environment with limited supervision.
• Familiarity with recognized data management and governance frameworks such as DAMA-DMBOK, DCAM, or similar frameworks.
• Understanding of consumer-packaged goods data, including product hierarchies, SKU proliferation, and regulatory data requirements, is preferred.
• Familiarity with AI-enabled metadata classification and tagging techniques is preferred.
• Exposure to AI governance, responsible AI principles, or data requirements for AI and machine-learning use cases is preferred.
• Artificial Intelligence Governance Professional certification is preferred.

About the team.

This role is part of McCain’s Global Data Governance team, which enables regional and global business functions to adopt consistent, sustainable, and trusted data practices.

The Principal Data Quality and Governance Engineer operates as an experienced individual contributor and works closely with business data owners, data stewards, data engineering, enterprise architecture, analytics, information security, IT teams, and regional business stakeholders. The role provides technical leadership and subject-matter expertise across data quality, metadata management, lineage, classification, governance technology, and data protection.

About McCain.

• Click Here to learn more about McCain and how we provide opportunities to make an impact that matters.

Leadership principles.

At McCain, our leadership principles guide how we engage with customers, collaborate as a team, and achieve success. We focus on understanding customer needs, driving innovation, empowering people, and taking ownership to clear obstacles and deliver results.

AI & Digital Capabilities.

At McCain, AI and digital capabilities are part of how we work and innovate. We value curiosity toward emerging technologies and the thoughtful, responsible use of AI-enabled tools to improve outcomes as part of our future-ready culture.

The McCain experience.

We are McCain. This statement is a testament to our collective strength and our individual value. Your contributions play a vital role in our success. Our winning culture is rooted in authenticity and trust, empowering us to bring out the best in one another. Here, you’ll find opportunities to learn, grow, and thrive. Join us and experience why we’re better together.

Our purpose is grounded in building meaningful relationships. We’re big believers in the power of working together in person. It helps us stay connected, collaborate more effectively, and grow as a team. At the same time, we recognize the importance of flexibility. Most office-based roles follow a hybrid model, with the option to work remotely two days a week. There may be exceptions depending on the role and location, so we encourage you to speak with your recruiter for more details.

Compensation Package: $85,500.00 - $114,000.00 . CAD annually + Bonus Eligibility 

The above reflects the target compensation range for the position at the time of posting. Hiring compensation will be determined based on experience, skill set, education and training, and other organizational needs. This posting is for an existing vacancy.