QlikSense Developer - Wholesale Banking

AI overview

Design and implement scalable QlikSense BI solutions in the Wholesale Banking sector, focusing on architecture, data modeling, and collaboration with key stakeholders.

Role Overview:

We are seeking an experienced QlikSense Developer with strong exposure to Wholesale Banking domain. The ideal candidate will be responsible for end-to-end BI solutioning including architecture, data modeling, dashboard design, and report development across Trade Finance, Business Banking, Wealth Management, and Transaction Banking portfolios.

Key Responsibilities:

  • Design and architect scalable QlikSense BI solutions aligned with Wholesale Banking business requirements.
  • Develop, enhance, and maintain interactive dashboards and reports using QlikSense.
  • Build robust data models, ETL scripts, and data transformations within Qlik environment.
  • Work closely with stakeholders from Trade Finance, Transaction Banking, Wealth, and Business Banking teams to translate requirements into technical solutions.
  • Optimize performance of Qlik applications for large-scale banking datasets.
  • Implement data governance, security rules, and access controls in QlikSense.
  • Perform data validation, reconciliation, and ensure high data accuracy standards.
  • Support UAT, production deployment, and ongoing enhancements.
  • Collaborate with data engineers and architects for integration with enterprise data warehouse and cloud platforms.

Mandatory Skills & Experience:

  • 5-10 years of experience in QlikSense development and data analytics space.
  • Strong Wholesale Banking domain experience (Trade Finance, Business Banking, Wealth, Transaction Banking).
  • Expertise in Qlik scripting, data modeling (star/snowflake schema), and performance tuning.
  • Strong SQL knowledge and experience working with large datasets.
  • Experience in data warehouse concepts and banking KPIs.
  • Understanding of regulatory and MIS reporting in banking environment.
  • Experience integrating Qlik with cloud / enterprise data platforms is preferred.
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