Data Quality Analyst

Key Responsibilities:

• Design and implementdata quality rules, checks, and metricsacross multiple data sources and pipelines.
• Write advancedSQL queriesto perform data validation, profiling, and anomaly detection.
• Develop and maintainPython scriptsto automate data quality assessments and reporting.
• ApplyAI/ML techniques(e.g., clustering, outlier detection, pattern recognition) to identify hidden data quality issues and inconsistencies.
• Collaborate with data engineers, analysts, and business stakeholders to understand data flows and ensure data integrity.
• Build and maintaindata quality dashboardsand alerts to monitor ongoing data health.
• Document data quality processes, findings, and remediation steps in a structured and accessible format.
• Participate in the development ofdata quality frameworksand contribute to continuous improvement initiatives.
• SupportAI/ML model teamsby ensuring high-quality input data and identifying potential data biases or gaps.

Required Skills & Qualifications:

• Bachelors / masters degree in computer science, Data Science, Information Systems, or a related field.
• 3+ years of experience in data quality, data analytics, or data engineering roles.
• Strong command ofSQLfor data analysis and validation.
• Solid understanding ofData Warehousing concepts(ETL, schema design, data lineage).
• Proficiency inPythonfor scripting, automation, and data manipulation.
• Exposure toAI/ML techniquessuch as anomaly detection, clustering, or supervised learning.
• Experience withdata profiling toolsandquality monitoring platforms.
• Familiarity with cloud data platforms (e.g., Azure , snowflake)
• Excellent analytical, problem-solving, and communication skills.