Data Management Platform Modernisation for Scalable, Secure, and Automated Operations

The client’s existing data management platform is underperforming, with outdated documentation, significant technical debt, and a lack of automated monitoring and testing frameworks. It struggles to handle increasing data volumes, leading to performance bottlenecks, security vulnerabilities, manual operational inefficiencies, and limited capacity for growth and integration testing.

A mid to large-sized financial institution requiring a robust data platform to support trading, risk management, and data analytics, with needs for performance, security, and scalability.

• Improve system performance to enable faster data processing and reduce bottlenecks.
• Enhance platform security to meet modern compliance standards and reduce vulnerabilities.
• Automate testing and monitoring processes to increase reliability and detect issues proactively.
• Establish a scalable architecture supporting future data growth and feature expansion.
• Streamline deployment pipeline to facilitate rapid, controlled releases and updates.

• Code refactoring and performance optimization for existing data management codebase.
• Implementation of automated testing frameworks including unit and regression tests.
• Real-time system monitoring and alerting integrated with performance tracking tools.
• Automated deployment pipelines to enable continuous integration and delivery.
• Configuration management supporting multiple environments (test, staging, production).
• Facilitation of seamless integration with pre-production testing environments for validation.

• Monitoring and alerting systems for proactive system performance management.
• Testing frameworks for automated regression and unit testing.
• Configuration management tools for environment-specific deployment settings.

• Support for handle increasing data volumes with minimal performance degradation.
• System uptime and reliability targets (e.g., >99.9% availability).
• Security standards compliance, including vulnerability reduction and secure deployment practices.
• Automated deployment processes to reduce manual errors and deployment time.
• Effective monitoring for system health and issue detection in real-time.

The project aims to significantly enhance operational efficiency by automating testing and deployment processes, leading to faster release cycles. It is expected to improve system performance and reliability, reduce security vulnerabilities, and establish a scalable architecture to support substantial data volume growth. These improvements will support better trading and risk management decisions, ensure compliance, and position the organization for future growth.