Data Quality Analyst
2 weeks ago
Key Responsibilities:
- Design and implement data quality rules, checks, and metrics across multiple data sources and pipelines.
- Write advanced SQL queries to perform data validation, profiling, and anomaly detection.
- Develop and maintain Python scripts to automate data quality assessments and reporting.
- Apply AI/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 maintain data quality dashboards and alerts to monitor ongoing data health.
- Document data quality processes, findings, and remediation steps in a structured and accessible format.
- Participate in the development of data quality frameworks and contribute to continuous improvement initiatives.
- Support AI/ML model teams by ensuring high-quality input data and identifying potential data biases or gaps.
Required Skills & Qualifications:
- Bachelor's / master's 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 of SQL for data analysis and validation.
- Solid understanding of Data Warehousing concepts (ETL, schema design, data lineage).
- Proficiency in Python for scripting, automation, and data manipulation.
- Exposure to AI/ML techniques such as anomaly detection, clustering, or supervised learning.
- Experience with data profiling tools and quality monitoring platforms.
- Familiarity with cloud data platforms (e.g., Azure , snowflake)
- Excellent analytical, problem-solving, and communication skills.
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