Java Engineer – Cloud-Native Financial Data Systems
Job Description
Our clients institutional financial technology division plays a key role in driving data and platform strategy across their organization.
The team is responsible for building and maintaining a data platform that manages, processes, and distributes trading, revenue, risk, and reference data, including client, product, and pricing information for our clients.
As a central source of critical datasets, the platform is heavily involved in data engineering, modeling, processing, visualization, and analytics.
The role involves developing user-facing, high-performance applications that operate on large-scale, real-time data systems using technologies such as Java, Angular, and Python. The platform leverages multiple data stores and processing frameworks, including both relational and NoSQL databases, as well as distributed data processing solutions.
They operate in a global, agile, and collaborative environment, working closely with stakeholders and their clients to set priorities and deliver scalable solutions. Responsibilities include implementing efficient caching and messaging strategies, as well as designing intuitive, enterprise-level data models by understanding the full lifecycle of financial products and end-to-end processing flows.
Our clients institutional financial technology division plays a key role in driving data and platform strategy across their organization.
The team is responsible for building and maintaining a data platform that manages, processes, and distributes trading, revenue, risk, and reference data, including client, product, and pricing information for our clients.
As a central source of critical datasets, the platform is heavily involved in data engineering, modeling, processing, visualization, and analytics.
The role involves developing user-facing, high-performance applications that operate on large-scale, real-time data systems using technologies such as Java, Angular, and Python. The platform leverages multiple data stores and processing frameworks, including both relational and NoSQL databases, as well as distributed data processing solutions.
They operate in a global, agile, and collaborative environment, working closely with stakeholders and their clients to set priorities and deliver scalable solutions. Responsibilities include implementing efficient caching and messaging strategies, as well as designing intuitive, enterprise-level data models by understanding the full lifecycle of financial products and end-to-end processing flows.