• Design and implement robust data governance frameworks and standards.
• Ensure high data quality, integrity, and security across all organizational data assets.
• Collaborate with cross-functional teams to define and enforce data governance policies.
• Lead data governance initiatives and projects, ensuring alignment with business objectives.
• Oversee data stewardship efforts and provide guidance to data stewards.
• Conduct regular data quality assessments and implement improvement plans.
• Manage data governance tools and support their effective utilization.
• Provide expert advice and training on data governance best practices.
• Monitor compliance with data governance policies and regulations.
• Stay current with industry trends and innovations in data governance to drive continuous enhancement.

• Strong communication, interpersonal, and presentation skills.
• Ability to multi-task and work under pressure.
• Excellent command of English.
• Excellent verbal and written communication skills; influencing skills and ability to work effectively in a geographically dispersed team.

• Data Quality Tools:

o Proficiency with data quality tools such as Informatica Data Quality, Talend Data Quality, IBM Info Sphere Quality Stage, or Apache Griffin.

• Data Profiling:

o Skills in data profiling techniques to assess data quality, including completeness, accuracy, consistency, and uniqueness.

• ETL Processes:

o Understanding of ETL (Extract, Transform, Load) processes and tools for data integration and transformation.

• SQL:

o Advanced SQL skills for querying and validating data to identify data quality issues.

• Data Integration:

o Experience in integrating data from various sources and ensuring quality during data movement and transformation.

• Scripting Languages:

o Knowledge of scripting languages such as Python or R for automated data quality checks and data processing.
Analytical Skills

• Data Analysis:

o Ability to analyze data to identify trends, patterns, and anomalies that impact data quality.

• Problem Solving:

o Strong skills in diagnosing and resolving data quality issues and developing corrective actions.

• Critical Thinking:

o Ability to evaluate data quality problems and determine appropriate solutions or improvements.
Quality Frameworks and Standards

• Data Quality Frameworks:

o Familiarity with data quality frameworks and best practices, such as those outlined by DAMA-DMBOK or ISO standards.

• Data Governance:

o Understanding of data governance principles, including data stewardship, data ownership, and data management policies.
Project Management

• Requirement Gathering:

o Experience in capturing and understanding business requirements related to data quality.

• Project Execution:

o Skills in managing data quality initiatives, including planning, implementation, and monitoring