Data Analyst

Role Purpose:

The Data Analyst is responsible for ensuring the accuracy, integrity, and reliability of the organization's data. This role involves developing and implementing data quality standards, monitoring data quality metrics, and collaborating with various departments to address data quality issues. Plays a crucial role in maintaining high data quality to support informed decision-making and organizational effectiveness.

Roles & Responsibilities:

Data Quality Management

• Develop and enforce data quality standards and policies.
• Establish data quality metrics and key performance indicators (KPIs) to measure data quality levels.
• Monitor data quality metrics and generate regular reports to highlight data quality issues

Data Validation and Cleansing

• Perform data validation and cleansing to ensure data accuracy and consistency.
• Identify and rectify data discrepancies, errors, and anomalies.
• Implement data cleaning processes and automated data quality checks

Data Quality Improvement

• Collaborate with data owners and stakeholders to identify root causes of data quality issues.
• Develop and implement data quality improvement plans.
• Work with IT and data management teams to implement data quality tools and technologies

Data Governance

• Contribute to the development and maintenance of data governance frameworks.
• Ensure compliance with data governance standards and regulatory requirements

Stakeholder Collaboration

• Work closely with business units, IT, and data stewards to ensure data quality requirements are met.
• Serve as a point of contact for data quality issues and inquiries

Documentation and Reporting

• Document data quality processes, procedures, and standards.
• Maintain comprehensive records of data quality assessments and improvement actions

Continuous Improvement

• Stay up to date with industry best practices and advancements in data quality management.
• Identify opportunities for continuous improvement in data quality processes.
• Promote a culture of data quality awareness and accountability within the organization.

Knowledge and Experience:

• Strong understanding of data quality principles, practices, and methodologies.
• Proficiency in data quality tools and technologies (e.g., data profiling, data cleansing, data validation).
• Excellent analytical skills with the ability to identify and resolve data quality issues.
• Strong communication and interpersonal skills. (is a plus)
• Attention to detail and a high level of accuracy.
• Ability to work collaboratively with cross-functional teams.
• Experience with data governance frameworks and practices.
• Knowledge of data management and database technologies (e.g., SQL, Tableau, Excel, Power BI, python etc.).

Education and Certifications

• Bachelor's degree in information management, Computer Science, Data Science, or a related field.
• Certification in programming language (python, SQL and R)  is a big plus.