Citi's Fixed Income Data team is seeking a Java engineer to architect and enhance real-time risk data acquisition, processing, and distribution frameworks. The role focuses on supporting global financial operations by delivering high-performance, resilient data platforms that enable real-time decision-making.
Requirements
- 7+ years of progressive experience in data engineering and software development, with a significant focus on building high-performance, large-scale distributed systems.
- Expert-level command of Java (version 11 or higher) with a deep understanding of concurrent programming, multithreading, advanced OOP concepts, design patterns, and performance tuning.
- Proven, hands-on production experience and deep architectural understanding of Apache Kafka or related technologies for high-throughput, fault-tolerant message queuing and streaming.
- Proven, hands-on production experience and deep architectural understanding of Apache Flink or related technologies for advanced real-time stream processing, complex event processing (CEP), and stateful computations.
- Proven, hands-on production experience and deep architectural understanding of Apache Pinot or related technologies for ultra-low-latency OLAP queries on streaming data.
- Strong expertise in designing and implementing highly available, scalable, and resilient distributed systems.
- Extensive experience with large-scale data storage solutions (e.g., S3, HDFS) and distributed query engines (e.g., Trino/Presto, Spark SQL).
Responsibilities
- Serve as the principal architect for scalable, high-performance Java-based real-time data solutions, ensuring robust design for high availability, fault tolerance, and resilience for both real-time and EOD risk processes.
- Drive the strategic implementation and optimization of distributed stream processing frameworks (Apache Kafka, Apache Flink) and real-time data storage technologies (Apache Pinot) for ultra-low-latency analytics and complex event processing.
- Lead the end-to-end design, development, and operation of real-time streaming data pipelines, integrating with large-scale object storage solutions like S3 and analytics engines such as Trino.
- Champion continuous improvement in data reliability, efficiency, and scalability. Establish and enforce best practices for code quality, performance optimization, and system resilience through hands-on leadership and thorough peer code reviews.
- Drive significant contributions across all phases of the Agile software development lifecycle, from architectural vision and detailed design to implementation, deployment, monitoring, and ongoing support for critical real-time data systems.
- Collaborate strategically with business analysts, product managers, quality assurance teams, and other engineering leads to ensure the delivery of seamlessly integrated, high-impact technology solutions.
- Stay abreast of industry trends and emerging technologies in real-time data processing, distributed systems, and cloud-native architectures, evaluating and proposing their adoption where beneficial.
Other
- Advanced Degree: Strong academic record, ideally with a Master's or Ph.D. in Computer Science, Electrical Engineering, or a related technical/quantitative discipline.
- Demonstrable success in architecting, leading, and delivering complex, multi-tiered, high-performance real-time data applications and platforms.
- A deep understanding of financial derivatives (with fixed income products) and risk analytics, or a strong demonstrable capability and eagerness to rapidly acquire expertise in this domain from a technical perspective.
- Exceptional communication, analytical, and problem-solving skills, with the ability to articulate complex technical concepts to diverse audiences and drive consensus on architectural decisions.
- Demonstrated experience leading technical initiatives and teams within an Agile software development environment.
