Data & Analytics Professional (Quality and Information Expert)

(1) DATA QUALITY PROFESSIONAL

This is supported by modern systems and tools. As part of the team, you act as the go-to person for anything related to credit risk data. Your job is to make sure this data is correctly loaded into the system and available on time. You will be working with people from different countries and backgrounds, so good communication is key. Your daily tasks include checking and fixing data issues, supporting others with data questions, using tools like SQL, SAS, MS Excel, Macros and Access, Power BI, Tableau, and R to monitor and improve data, helping test changes, collecting and checking data from different sources, and working with teams across locations to improve data quality.

(1) DATA QUALITY EXPERT

The Data Quality Expert plays a key role in supporting the company's global strategy to become a data-driven digital bank by ensuring high-quality, detailed data across the organization. Working with various teams—such as data owners, stewards, IT engineers, and operations—the expert helps define and implement data quality standards, monitors and analyzes data issues, and drives solutions to fix and prevent problems. The role also involves ensuring compliance with regulations, testing data quality tools, tracking key metrics, and promoting a culture of continuous improvement in how data is managed and used throughout the bank. Knowledge on Data Quality Management practices such as Data profiling, DQ Assessment, Data Cleansing, etc.

(1) DATA INFORMATION ANALYST

We are seeking for a Data Management Analyst to join their team, responsible for analyzing requirements from regulatory and business initiatives from start to finish. The role involves working closely with business data owners, stewards, and stakeholders to understand and refine data needs, translating them into clear business terms and developing conceptual data models. The analyst will help deliver key data standards, including business terms, data models, and mappings, contributing to company's global data definitions. They will also support and train colleagues on company's data terminology framework, maintain business terms and metadata, and assist in defining requirements for data quality, lineage, and governance. Experienced in SQL, data modeling, ETL, and data warehousing, with proficiency in tools such as Oracle, Hive, and Azure.

Industries:Human Resources

Function: Data Science