Software developer

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 re