Senior Data Quality Analyst

Required Skills & Competencies

• Advanced hands‑on experience with SQL, data querying, data profiling, and data analysis
• Strong practical understanding of data quality dimensions and how they appear in real datasets
• Hands‑on experience analyzing structured datasets across databases, spreadsheets, reporting extracts, data warehouses, or data lakes
• Working knowledge of data validation, reconciliation, exception analysis, duplicate detection, pattern analysis, and data sampling techniques
• Ability to interpret business rules and convert them into testable data conditions, validation logic, and expected outcomes
• Ability to investigate data anomalies using data evidence, business context, system behavior, and process knowledge
• Strong experience preparing data samples, issue evidence, exception lists, analytical summaries, and stakeholder‑ready findings
• Working knowledge of BI tools, reporting tools, profiling tools, data quality tools, or data catalog tools
• Good understanding of source systems, transformations, data pipelines, reporting layers, and how data movement can affect quality
• Ability to review analyst outputs and identify gaps in logic, evidence, completeness, or clarity
• Strong Excel and data manipulation capability
• Ability to explain technical data findings to non‑technical business stakeholders
• Good understanding of data governance, metadata, ownership, and stewardship concepts
• Strong documentation skills for rule analysis, issue evidence, data observations, and validation results