Job Description

We are seeking a Senior Java Engineer to join the team building our real-time market data platform. You will build, optimize, and maintain a high-performance, low-latency system that ingests, normalizes, and computes benchmark reference values from multiple external data sources. You will work in a fast-paced, collaborative environment with direct impact on the accuracy and reliability of financial data products consumed across the business.

Responsibilities

Implement composite reference-value algorithms that remain stable and representative under highly volatile input conditions.
Build and maintain aggregation methodologies (e.g., volume-weighted, time-weighted, median-based) used in downstream periodic calculations and risk reporting.
Deliver accurate, timely data feeds and calibration inputs to internal monitoring and control systems integrate new venue data sources on request to improve market coverage and resilience.
Conduct statistical and time-series analysis on high-frequency data to detect anomalies, latency patterns, and data-integrity issues.
Design low-latency capture, normalization, and cross-source synchronization of external real-time feeds.
Collaborate with DevOps and infrastructure teams to deploy production-ready Java code on trading systems.
Backtest and monitor model outputs propose data-driven improvements to accuracy and robustness.
Document methodologies and contribute to internal pricing standards across the firm.
Support business operations, including on-call troubleshooting of pricing issues and onboarding new instrument listings.

Requirements

Interest in global capital markets and quantitative/systematic data analysis.
5+ years of hands-on experience with Java development.
Experience with real-time or high-throughput data systems.
Strong understanding of multi-threading, concurrency, and low-latency system design.
Solid grasp of data structures, algorithms, and design patterns.
Strong analytical, problem-solving, and communication skills.

Nice to Haves

Experience with real-time market data feeds or exchange APIs (REST/WebSocket).
Familiarity with derivative instrument data (e.g., futures, contract specifications, reference rates).
Cloud platform experience (AWS).
SQL and NoSQL databases.
Python for backtesting, analysis, or tooling.
Understanding of monitoring, alerting, and control systems for real-time pipelines.
Spring Boot or similar Java backend frameworks.

Perks & Benefits