Data Quality Engineer

Key Responsibilities:

• Develop Data Quality Strategy: Establish and maintain enterprise-wide DQ frameworks, rules, and KPIs.
• Define and Govern CDEs:
• Identify, document, and classify Critical Data Elements (CDEs) in collaboration with business and technical stakeholders.
• Ensure CDEs are aligned with business processes, regulatory requirements, and strategic goals.
• Monitor and report on CDE-specific DQ KPIs to ensure they meet required standards.
• Design & Implement DQ Rules: Create validation rules and profiling checks for both general datasets and CDEs.
• DQ Monitoring & Reporting: Develop DQ dashboards and scorecards to track quality dimensions (accuracy, completeness, timeliness, consistency, uniqueness, validity).
• Root Cause Analysis: Investigate data quality issues impacting CDEs and recommend technical or process-oriented remediation actions.
• Metadata & Lineage: Ensure CDEs are linked to metadata repositories and data lineage tools for full traceability.
• Collaboration: Work with data owners, data stewards, and governance committees to prioritize DQ initiatives around CDEs.
• Compliance Support: Ensure CDEs comply with regulatory frameworks (e.g., PDPL, GDPR, HIPAA, ISO standards).
• Tool Expertise: Administer and leverage Data Quality and Governance platforms (Informatica Axon, Collibra, Talend DQ, etc.) to manage DQ rules and CDE repositories.

Qualifications & Experience

• Bachelor’s degree in computer science, Data Management, or related fields.
• 3–7 years of experience in Data Quality, Data Governance, or Master Data Management.
• Proven experience in:
• Identifying, defining, and governing CDEs.
• Establishing DQ metrics for CDEs.
• Profiling, cleansing, and validating datasets with a focus on CDEs.
• Knowledge of Data Governance frameworks (DAMA-DMBOK) and regulatory standards (PDPL, GDPR, etc.).
• Familiarity with enterprise data platforms, metadata repositories, and lineage tools.