Description

You will lead end-to-end data cleansing, standardization, and quality improvement initiatives across large-scale, complex datasets.

This role is on-site.

Responsibilities

• Lead data profiling and anomaly detection to identify inconsistencies, duplicates, and integrity issues across multiple systems.
• Define and enforce enterprise data quality rules, transformation logic, and standardized cleansing playbooks.
• Develop and manage work plans, timelines, and budgets for data quality and cleansing projects.
• Maintain thorough documentation of profiling reports, transformation methodologies, and remediation plans for audit and compliance.
• Collaborate with data stewards and stakeholders to prioritize and remediate data quality issues.

Required Skills

• 12+ years of experience in data quality management, cleansing, and standardization.
• Expert-level proficiency in Azure Data Factory (ADF) for designing and automating scalable cleansing workflows.
• Strong hands-on experience with Azure SQL databases, data marts, and data warehouse design.
• Proven expertise in ETL/ELT pipeline design and optimization.
• Advanced SQL-based data extraction, transformation, and validation skills.
• Experience with Azure, Snowflake, or AWS cloud environments.
• Working knowledge of Oracle, Teradata, NoSQL, or Hadoop environments.
• Experience applying Kimball and Inmon modeling methodologies.
• Bachelor's degree in Computer Science, Information Systems, Data Analytics, or a related discipline.

Preferred Skills

• Master's degree in a related technical discipline.
• Exposure to enterprise data governance frameworks and large-scale data management environments.

Key Skills

Education

Bachelor's degree