{"id":188560,"url":"https://alion.io/job/cube-data-quality-analyst","title":"Data Quality Analyst","company":{"id":172162,"name":"CUBE","domain":"cube.global","url":"https://alion.io/company/cube-3","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":92,"open_postings":5,"ghost_share":0,"stale_share":0.2,"repost_share":0.2,"time_to_fill_p50_days":32,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Analytics","role_family":"Analytics","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Puducherry, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"ETL/ELT","optional":false},{"name":"MS SQL","optional":false},{"name":"SQL","optional":false},{"name":"SSIS","optional":false}],"status":"live","first_seen_at":"2026-09-02T04:51:05Z","employer_posted_date":"2026-09-02","last_verified_at":"2026-11-01T05:27:13Z","board_verified":true,"closed_at":null,"days_open":60,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":60},"description":"CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS solutions, powered by AI, to simplify the complex and everchanging world of compliance for our clients.\nWhy us?\nCUBE is a globally recognized brand at the forefront of Regulatory Technology. Our industry-leading SaaS solutions are trusted by the world’s top financial institutions globally.\nIn 2024, we achieved over 50% growth, both organically and through two strategic acquisitions. We’re a fast-paced, high-performing team that thrives on pushing boundaries-continuously evolving our products, services, and operations. At CUBE, we don’t just keep up we stay ahead.\nWe believe our future is built by bold, ambitious individuals who are driven to make a real difference. Our “make it happen” culture empowers you to take ownership of your career and accelerate your personal and professional development from day one.\nWith 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.\nWe 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.\nPurpose\nThe 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.\nThis 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.\nWorking 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.\nThe 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. \nBy 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.\nKey Responsibilities\nProfile data, design and execute data quality rules, and monitor scorecards and dashboards to identify issues, trends, and areas requiring corrective action. \nInvestigate 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\nApply 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. \nDesign and implement improvements to the existing data ingestion pipelines and post load validation to increase efficiency and reduce risk of pipeline failures.\nSupport remediation activity through SSIS/ETL workflows, working with technology teams to ensure data fixes are implemented safely and consistently across relevant systems. \nMaintain documentation for data quality rules, thresholds, lineage, controlled correction procedures, remediation actions, and operating processes. \nCollaborate with business, technology, and compliance teams to align data quality activity, remediation approaches, and controlled data corrections with regulatory and operational needs.\nSkills & Competencies\nStrong analytical/problem-solving skills; attention to detail and data integrity.\nProficiency 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.\nDevelop Stored procedures to further detect and trigger automated correction of erroneous data within Production and Live SQL Servers.\nUnderstanding of data quality frameworks, data governance, and regulatory expectations. \nClear communication, stakeholder collaboration, and a customer focused mindset. \nOpenness to AI enabled tools to improve monitoring, triage, and remediation.\nRequired Experience & Qualifications\nExperience in data quality, data operations, or BI/MDM within data critical environments (financial services advantageous).\nHandson exposure to MS SQL Server, Excel, and familiarity with SSIS or similar ETL tools. \nKnowledge of data governance principles; experience with DQ tooling and/or data catalogues desirable. \nRelevant degree (data, IT, business, or related) or equivalent experience; certifications (e.g., DAMA/CDMP, Microsoft) a plus.\nPerformance Indicators\nImprovement in data quality scores (accuracy, completeness, consistency) and reduction in recurring defects. \nSLA adherence for issue triage and remediation; reduced backlog and rework. \nPositive stakeholder feedback on responsiveness and clarity; fewer escalations. \nStrong audit/compliance outcomes and UpToDate documentation. \nDemonstrated use of AI/automation to increase coverage, speed, or accuracy in DQ controls.\nInterested?\nIf 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.\nCUBE is an equal opportunity employer. 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