Requirements

Expected technologies

SQL

Microsoft Power BI

Optional technologies

Python

R

Java

Scala

Our requirements

• Proven experience in data management, data quality, or a similar role, ideally in financial services
• Strong command of advanced SQL queries and familiarity with one or more programming languages (e.g., Python, R, Java, Scala)
• Understanding of data taxonomy and ability to build small-scale data models
• Proficiency in Power BI for report creation
• Excellent stakeholder management skills; ability to work across IT, Architecture, Financial Crime, Compliance, Legal, and Business units
• Experience in financial crime domains (AML, KYC, Transaction Monitoring, Sanctions), agile methodologies, and SAFe is an advantage
• Professional, organized, and detail-oriented; committed to high-quality outcomes and optimal solutions
• Strong analytical and problem-solving skills with a focus on data accuracy
• Effective communicator with both technical and non-technical stakeholders
• Ability to work both independently and collaboratively
• Fluency in English (spoken and written) required

Optional

• Familiarity with data governance frameworks and methodologies is a plus
• Experience with data migration and integration projects is a plus

Your responsibilities

• Analyze existing KYC data to identify gaps, inconsistencies, and improvement areas
• Collaborate with business and IT stakeholders across units to develop and implement data standards
• Participate in major projects for the delivery of the Group KYC Tool
• Cooperate with Data Architects and SMEs to create and maintain Business Information Models (BIM) aligned across the enterprise
• Monitor data quality metrics and report findings to management
• Investigate and resolve data quality issues, escalating complex cases as needed
• Provide consultative services to agile delivery teams, ensuring adherence to data governance best practices
• Support implementation of new KYC systems and processes, focusing on accurate data migration and integration
• Use enterprise-approved tools to build reproducible data flows for reporting purposes
• Implement testing, monitor data flow and reporting quality, perform necessary upgrades and maintenance
• Collaborate with various stakeholders to analyze and visualize complex data clearly and accurately
• Document data definitions, data lineage, and data quality rules
• Participate in data governance/stewardship communities of practice
• Contribute to development and maintenance of data governance policies and procedures
• Stay updated on KYC data management regulations and best practices
• Proactively identify opportunities for data quality and efficiency improvements