Data Quality Analyst
About the job
- Strong analytical and problem-solving skills, attention to detail, and commitment to data integrity.
- Proficiency in Microsoft Excel, including advanced formulas and pivot tables.
- Advanced Microsoft SQL Server knowledge, including DDL, DML, and TCL commands, with robust testing and quality assurance of production scripts.
- Familiarity with SQL Server Integration Services or similar extract, transform, and load tools and workflows.
- Ability to develop stored procedures to detect erroneous data and trigger automated corrections within production and live SQL servers.
- Understanding of data quality frameworks, data governance principles, and regulatory expectations.
- Experience in data quality, data operations, or business intelligence/master data management within data-critical environments.
- Hands-on experience with Microsoft SQL Server and Excel, and familiarity with SQL Server Integration Services or similar extract, transform, and load tools.
- A relevant degree in data, information technology, business, or a related field, or equivalent experience.
- 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, Microsoft SQL Server, and SQL Server Integration Services, assess the impact of data issues, and determine remediation steps against the production golden data source and live customer-facing databases.
- Apply controlled data corrections where required, ensuring changes are accurate, authorized, traceable, and completed according to governance standards, approval processes, and audit requirements.
- Design and implement improvements to data ingestion pipelines and post-load validation to increase efficiency and reduce the risk of pipeline failures.
- Support remediation through SQL Server Integration Services and extract, transform, and load workflows, working with technology teams to implement data fixes 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 activities, remediation approaches, and controlled data corrections with regulatory and operational needs.
- Financial services experience is advantageous.
- Experience with data quality tooling and data catalogues is desirable.
- Certifications such as DAMA/CDMP or Microsoft certifications are a plus.
- Openness to AI-enabled tools for improving monitoring, triage, and remediation.
About the company
CUBE provides automated regulatory intelligence via a subscription platform that helps regulated firms stay compliant by mapping regulatory changes to each client’s business profiles and control frameworks. Its AI continuously scans regulatory sources, extracts relevant rules, and translates them into concrete compliance actions linked to a company’s risk profile and internal controls. Unlike generic alert services, CUBE offers ongoing regulatory mapping tied to a client’s actual risk and control setup, and it emphasizes sustainability with a remote operating model. The goal is to give regulated firms timely, practical regulatory guidance to reduce risk and support positive societal outcomes through responsible technology.
Company Size
501-1,000
Company Stage
Growth Equity (Venture Capital)
Total Funding
$12.8M
Headquarters
London, United Kingdom
Founded
2011
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Simplify's Take
What believers are saying
- September 16, 2026 IBM partnership puts CUBE inside enterprise governance workflows immediately.
- CUBE says September 2026 it serves about 1,000 customers across regulated industries.
- Agentic Coworker expansion on September 2, 2026 widens workflows beyond regulatory monitoring.
What critics are saying
- IBM, Microsoft, and ServiceNow can squeeze CUBE into a replaceable data supplier role.
- Four acquisitions since March 2024 create integration debt and product confusion through 2027.
- A missed EU AI Act update will trigger client losses, audits, and legal exposure.
What makes CUBE unique
- CUBE tracks regulatory sources across every country and published language, per September 2026 leadership page.
- IBM embedded CUBE data into watsonx.governance on September 16, 2026.
- Acquisitions of Reg-Room, Acin, Kodex AI, and 4CRisk built one compliance platform.
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Benefits
Hybrid Work Options
Growth & Insights and Company News
6 month growth
0%1 year growth
1%2 year growth
2%IBM Adds AI Rule Monitoring to watsonx.governance. IBM announced Regulatory Horizon Scanning with CUBE on September 16, 2026, bringing global AI-regulatory updates into watsonx.governance workflows. September 20, 2026 Key points * 01 IBM announced Regulatory Horizon Scanning for IBM watsonx.governance on September 16, 2026, through an integration with CUBE. * 02 The capability is designed to continuously monitor AI-related regulatory developments from regulators, lawmakers, standards organizations and industry associations. * 03 Teams can map regulatory changes to AI systems, models, use cases, policies and controls, then assign actions and track remediation. * 04 The workflow is intended to maintain a traceable record of how regulatory changes were assessed and addressed. IBM and CUBE announced Regulatory Horizon Scanning for watsonx.governance, linking global AI-rule updates to systems, policies and audit workflows. IBM announced Regulatory Horizon Scanning for IBM watsonx.governance on September 16, 2026, adding CUBE's global regulatory intelligence to the platform's AI-governance workflows. The capability is designed to track AI-related regulatory developments, connect them to an organization's systems and controls, and turn the resulting assessments into documented work. IBM brings AI-rule monitoring into watsonx.governance. Regulatory Horizon Scanning is a capability within IBM watsonx.governance, not a separate product. CUBE supplies the integrated regulatory-intelligence data, while IBM places that information inside the governance platform's existing workflow. The focus is practical: instead of treating regulatory monitoring as a separate legal-research task, teams can work with updates alongside their AI inventories, policies and controls. IBM describes the monitored landscape through examples such as the EU AI Act, national AI laws, regulatory guidance, standards and regulatory interpretations. Machine Learning & Artificial Intelligence What Regulatory Horizon Scanning is designed to monitor. The capability is designed to continuously monitor global AI-related regulatory developments. IBM identifies four source categories: regulators, legislative bodies, standards organizations and industry associations. That scope gives governance teams a stream of regulatory updates to evaluate against their own AI estate. The announcements describe global monitoring, while the workflow centers on the organization's concrete systems, models and use cases. From a regulatory change to a governance task. The announced workflow connects a regulatory development with the parts of an AI program that may be affected. Teams can map an update to: * AI systems and models; * AI use cases; * policies and controls; and * governance activities. From there, the capability supports impact evaluations, assessments, assigned actions, documented decisions and remediation tracking. The intended result is a traceable record of how an organization evaluated a regulatory change and addressed it. That link between discovery and follow-through is the important shift in IBM's announcement. Finding a new rule is only the first step; the governance workflow is where a team records its assessment and assigns the resulting work. What the watsonx.governance interface puts in view. The watsonx.governance interface presents Regulatory Horizon Scanning through dashboard panels, filters, charts and regulatory-change visualizations. The dashboard includes the labels "Regulatory Horizon Scanning" and "CUBE Regulatory Content," making the connection between the platform and CUBE's data visible in the interface. A separate walkthrough of IBM watsonx.governance shows a console with model-compliance categories, generative-AI quality metrics and a Regulatory Information area containing Applicability Assessments and Mandates. Those screens provide context for how regulatory information fits into the broader governance console. Why the workflow matters for enterprise AI teams. AI regulations change across jurisdictions, and the relevant question for an enterprise is rarely just whether a rule exists. Teams also need to determine which model, application, policy or control it affects and what action follows. Regulatory Horizon Scanning is designed to keep those steps connected: monitor developments, map them to AI assets, assess their impact, assign work, document decisions and track remediation. IBM and CUBE announced the collaboration as enterprises expand their use of AI and face a more complex regulatory environment. Other Languages Read this article in another available language.
CUBE, the AI-native regulatory intelligence company, has partnered with IBM to integrate its global regulatory intelligence into IBM watsonx.governance. The new Regulatory Horizon Scanning capability will provide enterprises with continuous visibility into regulatory developments affecting their AI systems worldwide. The integration monitors AI-related regulatory developments from regulators, legislative bodies, standards organisations, and industry associations globally. It enables organisations to map regulatory changes to governance use cases and maintain traceable records of assessments within existing workflows. London-based CUBE serves clients across Europe, the US, Canada, Asia, and Australia, including major financial institutions. The IBM collaboration follows partnerships announced earlier this year with Microsoft and ServiceNow, marking continued expansion for the company. The integration addresses growing regulatory complexity as organisations adopt generative and agentic AI, with requirements emerging from frameworks like the EU's AI Act and NIST AI Risk Management Framework.
SLS client 4CRisk is acquired by CUBE. Silicon Legal represented 4CRisk as they were acquired by CUBE. 4CRisk's AI-powered compliance and risk solutions help organizations navigate regulatory complexity and cut compliance costs.
CUBE, a global leader in automated regulatory intelligence, has acquired Silicon Valley-based RegTech firm 4CRisk. The deal expands CUBE's capabilities beyond financial regulation into corporate compliance domains including cyber, AI, privacy, labour laws and ESG. Founded in 2019, 4CRisk uses specialised AI language models to map corporate policies and procedures directly to regulatory obligations, controls and risks, delivering results up to 50 times faster than manual processes. The company's AI compliance assistant, Ask ARIA, provides highly accurate automation. The acquisition strengthens CUBE's position as it builds a unified, AI-powered compliance and risk platform. CUBE now serves over 1,000 customers globally across financial services and adjacent industries. Both companies were named in the RegTech100 for 2026. Transaction details were not disclosed.
/PRNewswire/ -- CUBE ACQUIRES BERLIN-BASED KODEX AI, CREATING AN INDUSTRY-FIRST UNIFIED COMPLIANCE, RISK AND AGENTIC AI PLATFORM