Specialist, Data Quality Developer

You are a senior, detail-oriented data professional with strong technical expertise in data quality, data governance, data cataloging, stewardship, privacy, and security. You thrive in complex environments, work with minimal supervision, and are passionate about delivering reliable, high-quality data solutions end to end. You bring strong analytical thinking, collaboration skills, and the ability to translate business requirements into scalable technical solutions. You are comfortable working across cross-functional teams and enjoy continuous learning in modern data technologies. In This Role, You Will: Data Quality & Development Design, build, and maintain data quality pipelines for profiling, validation, cleansing, enrichment, and monitoring Independently define, configure, deploy, test, and operationalize enterprise data quality rules, thresholds, scorecards, and controls Develop exception handling, remediation workflows, root-cause analysis processes, and issue management mechanisms to improve data quality outcomes Automate data quality checks to improve reliability, reduce manual effort, and support production operations Optimize performance, scalability, resiliency, and fault tolerance of data quality solutions Bachelor's degree in computer science, Data Science, Software Engineering, or a related field Certification in Data Management (e.g., DAMA) - preferred Cloud certifications (Azure) and data engineering certifications - preferred 8+ years of experience in data development, data quality, data governance, or data management Strong experience designing, configuring, and implementing enterprise data quality and MDM solutions from requirements through production support Experience implementing data cataloging, metadata management, glossary, lineage, and stewardship workflows in enterprise environments Experience working with privacy, data protection, and security controls for sensitive data, including masking, tokenization, and access management Proven ability to operate as a senior hands-on individual contributor, independently driving technical design and implementation with minimal supervision Strong experience collaborating with cross-functional teams including architects, governance leads, stewards, analysts, and business stakeholders Strong knowledge of enterprise Data Quality, MDM, data governance, data cataloging, and data stewardship practices Proven ability to define, configure, deploy, and operationalize data quality rules, controls, scorecards, and remediation workflows Experience with data catalog and metadata management capabilities including glossary, lineage, classification, and tagging Strong understanding of data governance frameworks, ownership models, critical data elements, and control monitoring Knowledge of data privacy and security techniques including tokenization, detokenization, masking, encryption, and access controls Proficiency in SQL, Python, and ETL/ELT tools Experience with Informatica (IDQ, MDM) and Azure Data Services; familiarity with catalog/governance tools such as Purview, Collibra, Atlan, or Informatica EDC is an asset Data modeling, integration, APIs, DevOps, and metadata/lineage expertise Strong analytical, problem-solving, communication, and stakeholder engagement skills Ability to manage multiple priorities in dynamic environments while working independently and driving outcomes end to end Design and implement MDM domain models, canonical data models, hierarchies, reference data structures, match/merge rules, and survivorship logic Develop ingestion, validation, stewardship, and publication pipelines to support trusted master data across systems Establish data standards, crosswalks, deduplication strategies, and data quality controls aligned to governance requirements for critical master data domains Support issue resolution, survivorship tuning, hierarchy maintenance, and ongoing operational support for enterprise MDM solutions Build integrations between DQ/MDM/catalog platforms and enterprise systems, APIs, data lakes, and cloud data platforms Implement and support data cataloging capabilities including metadata harvesting, lineage integration, glossary curation, classification, and tagging Support cloud-based data environments (e.g., Azure) and ensure secure, compliant, and governed data movement across platforms Apply data security techniques such as tokenization, detokenization, masking, encryption, and access controls for sensitive and regulated data Implement and enforce data governance policies, standards, controls, and operating model requirements across critical data domains Apply data privacy principles and regulatory requirements by supporting sensitive data identification, classification, retention, minimization, and compliant handling practices Monitor data quality KPIs, issue trends, and control effectiveness, and implement alerting and remediation mechanisms Maintain metadata, lineage, audit trails, governance artifacts, and compliance documentation to support transparency and traceability Deliver trusted datasets for reporting, analytics, and AI use cases Ensure data integrity across dashboards and reporting environments Support adoption of DQ/MDM tools and processes across the organization