Data Quality Analyst

🌐 With over 700 CUBERs across 19 countries spanning EMEA, the Americas, and APAC, we operate as one team with a shared mission to transform regulatory compliance. Diversity, collaboration, and purpose are the heartbeat of our success.

💡 We were among the first to harness the power of AI in regulatory intelligence, and we continue to lead with our cutting-edge technology. At CUBE, You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance.

Purpose
The Data Quality Analyst plays a critical role in ensuring the organisation maintains accurate, complete, and reliable data that underpins the core Cube product, its golden data source, regulatory compliance, reporting, analytics, automated decisioning, and operational efficiency.
This role is responsible for identifying, investigating, and resolving data quality issues across key systems. This includes assessing data errors, determining root causes, implementing robust remediation actions, and applying controlled corrections to data and ingestion procedures in line with agreed governance standards, approval processes, and audit requirements. The Data Quality Analyst ensures that any data amendments are accurate, traceable, and completed in a controlled manner to protect the integrity of enterprise data.

Working closely with technology, product, and operational business teams, the Data Quality Analyst applies data governance standards, data quality rules, and analytical techniques to improve the accuracy, consistency, and usability of data. The role also supports the adoption of AI-enabled monitoring and anomaly detection tools to improve the speed and accuracy of data quality operations.

The data quality analyst will utilise analysis of existing ingestion processes and BAU processes to implement improvements that enhances the deliverables, removes routine manual work and reduces margin for error.

By improving the quality of data that underpins the Cube product and customer journeys, the Data Quality Analyst plays an essential part in enhancing customer experience, preventing downstream errors, and ensuring customers receive accurate, timely, and dependable services.

Key Responsibilities
•  Profile data, design and execute data quality rules, and monitor scorecards and dashboards to identify issues, trends, and areas requiring corrective action.
•  Investigate data anomalies and root causes using Excel, MSSQ and SSIS, assessing the impact of data issues and determining appropriate remediation steps against the production golden data source and LIVE customer facing databases
•  Apply controlled corrections to data where required, ensuring changes are accurate, authorised, traceable, and completed in line with agreed governance standards, approval processes, and audit requirements.
•  Design and implement improvements to the existing data ingestion pipelines and post load validation to increase efficiency and reduce risk of pipeline failures.
•  Support remediation activity through SSIS/ETL workflows, working with technology teams to ensure data fixes are implemented safely and consistently across relevant systems.
•  Maintain documentation for data quality rules, thresholds, lineage, controlled correction procedures, remediation actions, and operating processes.
•  Collaborate with business, technology, and compliance teams to align data quality activity, remediation approaches, and controlled data corrections with regulatory and operational needs.

Skills & Competencies
•  Strong analytical/problem-solving skills; attention to detail and data integrity.
•  Proficiency in Excel (advanced formulas, pivot tables), advanced MSSQL including the use of DDL , DML and TCL commands within the constraints of the role with robust testing/QA of all production scripts and familiarity with SSIS/ETL flows.
•  Develop Stored procedures to further detect and trigger automated correction of erroneous data within Production and Live SQL Servers.
•  Understanding of data quality frameworks, data governance, and regulatory expectations.
•  Clear communication, stakeholder collaboration, and a customer focused mindset.
•  Openness to AI enabled tools to improve monitoring, triage, and remediation.

Required Experience & Qualifications
•  Experience in data quality, data operations, or BI/MDM within data critical environments (financial services advantageous).
•  Handson exposure to MS SQL Server, Excel, and familiarity with SSIS or similar ETL tools.
•  Knowledge of data governance principles; experience with DQ tooling and/or data catalogues desirable.
•  Relevant degree (data, IT, business, or related) or equivalent experience; certifications (e.g., DAMA/CDMP, Microsoft) a plus.

Performance Indicators
•  Improvement in data quality scores (accuracy, completeness, consistency) and reduction in recurring defects.
•  SLA adherence for issue triage and remediation; reduced backlog and rework.
•  Positive stakeholder feedback on responsiveness and clarity; fewer escalations.
•  Strong audit/compliance outcomes and UpToDate documentation.
•  Demonstrated use of AI/automation to increase coverage, speed, or accuracy in DQ controls.

Interested?

If you are passionate about leveraging technology to transform regulatory compliance and meet the qualifications outlined above, we invite you to apply. Please submit your resume detailing your relevant experience and interest in CUBE.​

CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.