Data Quality Analyst

About the job: Welcome to MultiBank Group; a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We excel in providing cutting-edge trading technology, unparalleled liquidity, and exceptional customer service, offering an extensive range of financial products such as Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.Join our thriving community of over 1 million clients across 90 countries, contributing to a daily trading volume exceeding US$ 12.1 billion. As a heavily regulated (11 financial regulators across 5 continents), award-winning, and reliable financial institution, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.Seize the opportunity to work with a rapidly growing, world-class team spanning more than 20 countries, driven by innovation, collaboration, and customer focus.

Role Overview: As a Data Quality Analyst, you will be responsible for ensuring the accuracy, completeness, and consistency of data within an organization. Your role involves analyzing datasets/reports, identifying discrepancies or errors, and implementing processes to improve data quality. By maintaining high standards of data integrity, you will support decision-making processes and enable effective business operations.

Key Responsibilities:

• Data Analysis: Analyze large datasets to identify data quality issues, anomalies, and trends using statistical methods and data profiling techniques.
• Data Cleansing: Develop and implement data cleansing procedures to address inaccuracies, duplicates, and inconsistencies in data sets, ensuring data integrity and reliability.
• Quality Assurance: Establish data quality standards, guidelines, and best practices to maintain consistency and accuracy across databases and systems.
• Data Validation: Validate data inputs, outputs, and transformations to ensure alignment with business requirements, data models, and quality standards.
• Root Cause Analysis: Investigate the root causes of data quality issues and collaborate with stakeholders to implement corrective actions and prevent recurrence.
• Process Improvement: Identify opportunities to streamline data management processes, enhance data quality controls, and optimize data workflows to improve efficiency and accuracy.
• Documentation: Document data quality rules, procedures, and outcomes, and maintain comprehensive documentation of data quality issues, resolutions, and validations.
• Training and Support: Provide training and support to end-users and data stakeholders on data quality principles, tools, and processes to promote a culture of data excellence.
• Reporting and Monitoring: Generate reports and metrics to track data quality metrics, monitor performance against established benchmarks, and communicate insights to stakeholders.

Qualifications:

• Education: Bachelor's degree in Computer Science, Information Systems, Mathematics, Statistics, or related field.
• Experience: 1-3 years of experience in data analysis, data management, or related roles, preferably in a data-intensive environment.
• Analytical Skills: Strong analytical and problem-solving skills, with the ability to analyze complex datasets, identify patterns, and draw meaningful insights.
• Technical Proficiency: Proficiency in SQL for querying and manipulating data, and experience with data analysis tools such as Excel and Python.
• Data Management: Understanding of data management principles, data governance, data quality frameworks, and best practices.
• Attention to Detail: Meticulous attention to detail and accuracy in data validation, cleansing, and analysis processes.
• Communication Skills: Excellent verbal and written communication skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.
• Team Collaboration: Ability to work collaboratively in cross-functional teams, sharing information, coordinating activities, and contributing to team goals.
• Continuous Learning: Willingness to learn and adapt to new technologies, tools, and methodologies in the field of data quality and management.