The Data Quality Specialist Lead Engineer will be responsible for developing and implementing data quality frameworks, governance standards, and validation processes across enterprise systems. This role requires strong expertise in data quality strategy, data profiling, data cleansing, metadata management, and master data management practices. The ideal candidate will work closely with cross-functional business, analytics, and engineering teams to improve data integrity, consistency, and reliability across the organization.
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Lead the design and implementation of enterprise data quality frameworks, controls, and governance processes.
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Develop data quality metrics, rules, workflows, dashboards, and scorecards to monitor and improve data health.
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Perform data profiling, data validation, cleansing, and issue remediation across multiple data sources and platforms.
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Partner with business and technical stakeholders to define data quality requirements, standards, and SLAs.
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Manage and resolve data quality issues, root-cause analysis, and continuous improvement initiatives.
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Lead large-scale data quality initiatives and ensure alignment with business objectives and compliance standards.
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Implement data validation solutions using industry tools and cloud platforms.
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Document data quality rules, data dictionaries, metadata, and data processes.
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Collaborate with Data Governance, Data Engineering, ETL, BI, and MDM teams to maintain data accuracy and reliability.
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Support data migration, integration projects, and data quality automation across enterprise systems.
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Minimum 12 years of experience in data quality, data engineering, or enterprise information management roles.
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Strong experience with data quality tools such as Informatica IDQ, Collibra, Talend, Ataccama, SAP Data Services, or similar.
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Deep knowledge of data profiling, data cleansing, ETL processes, and metadata management practices.
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Hands-on experience with SQL, database concepts, complex queries, stored procedures, and performance troubleshooting.
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Expertise working with data warehouses, BI reporting platforms, and cloud technologies (AWS, Azure, or GCP).
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Experience with MDM frameworks and enterprise-wide data governance.
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Strong analytical, communication, and stakeholder management skills.
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Background in leading data quality strategy and driving enterprise-level initiatives.