Requirements

Expected technologies

SAS

Python

PySpark

SQL

Hadoop

Jira

Confluence

Monday.com

Operating system

Windows

Linux

Our requirements

• Proven experience in a similar data analysis or data management role
• Bachelor’s degree in IT, Mathematics, or a related numerate discipline
• Proficiency in at least one tool: SAS, Python, PySpark, SQL, or Hadoop
• Strong understanding of data architecture and ETL pipeline development
• Experience in gathering business requirements and delivering analytical solutions
• Effective problem-solving and project management skills
• Ability to manage multiple priorities and work under tight deadlines
• Strong communication skills and ability to collaborate across global teams
• Experience with data governance and regulatory compliance principles
• Familiarity with JIRA, Confluence, or Monday.com for project tracking

Optional

• Master’s degree in a relevant field
• Experience with Prophecy or similar data orchestration tools
• Prior exposure to banking risk data, systems, and risk models
• Understanding of data privacy and security practices in financial environments
• Experience preparing presentations or dashboards for senior stakeholders
• Background in automation and scripting for process optimization
• Knowledge of Wholesale Credit Risk modeling requirements
• Ability to contribute to architectural discussions in a data engineering context

Your responsibilities

• Collating, testing, and validating independently sourced risk data
• Developing and maintaining ETL pipelines to support GRADE platform ingestion
• Assessing data quality issues and driving resolution with relevant stakeholders
• Collaborating with global teams to support BAU and project-based data tasks
• Creating clear visualizations and documentation for key business stakeholders
• Contributing to data architecture and business process roadmap design
• Supporting user onboarding, capacity management, and change initiatives
• Managing relationships across multiple functional teams and data consumers
• Driving continuous improvement across data processes and governance