Job Description
**Project Overview**
**This role is part of an initiative to build a real-time data pipeline for processing front-office markets chat data. The system will ingest unstructured messages from trading and sales desks, invoke NLP Engine APIs to extract intent and entities, and transform the results into structured objects. These outputs will power downstream use cases such as trade analytics, trade processing, pricing, risk management, and compliance monitoring. In addition to real-time capabilities, the initiative will also encompass batch processing using big data technologies like Apache Spark to handle large historical datasets, enable complex analytical workloads, and generate aggregated reports. The solution leverages Java, Spring Boot, Elasticsearch, Oracle, Kafka, Apache Spark, and caching frameworks to ensure scalability, low latency, high reliability, and efficient processing of both real-time and historical data in mission-critical trading environments.**
**Position ...
**This role is part of an initiative to build a real-time data pipeline for processing front-office markets chat data. The system will ingest unstructured messages from trading and sales desks, invoke NLP Engine APIs to extract intent and entities, and transform the results into structured objects. These outputs will power downstream use cases such as trade analytics, trade processing, pricing, risk management, and compliance monitoring. In addition to real-time capabilities, the initiative will also encompass batch processing using big data technologies like Apache Spark to handle large historical datasets, enable complex analytical workloads, and generate aggregated reports. The solution leverages Java, Spring Boot, Elasticsearch, Oracle, Kafka, Apache Spark, and caching frameworks to ensure scalability, low latency, high reliability, and efficient processing of both real-time and historical data in mission-critical trading environments.**
**Position ...
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