Lead Java Developer - FI Data

Lead Java Developer - FI Data

Working at Citi is more than just a job. It is a chance to join a team of over 230,000 people from around the globe. At Citi, you'll have the opportunity to grow your career, give back to your community, and make a real impact.

Job Overview

The Fixed Income Data team is a strategic and integral part of supporting Citi's GSP/Rates businesses, delivering exceptional capabilities in advanced business analysis, strategic project management, cutting-edge application development, robust quality assurance, and seamless integration with proprietary technology solutions. Our mission is to architect, build, and operate high-performance, resilient data platforms that empower critical financial operations and drive real-time decision-making across the firm.

The Opportunity

We are seeking a highly accomplished Java engineer to join our Realtime Risk Data team. This role is at the forefront of architecting, leading, and significantly enhancing our comprehensive real-time risk data acquisition, processing, and distribution framework. You will serve as a technical thought leader, driving the strategic adoption and implementation of cutting-edge streaming technologies such as Apache Kafka for high-throughput data ingestion, Apache Flink for complex event processing and real-time analytics, and Apache Pinot for ultra-low-latency OLAP queries on large datasets. You will also oversee the management of petabyte-scale datasets on S3, enabling efficient querying via Trino. This role demands deep technical expertise, a strategic mindset, and the ability to mentor and guide engineering teams in designing, developing, and optimizing mission-critical, high-performance real-time data solutions that directly impact global financial operations.

Key Responsibilities

• Architectural Leadership: 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.
• Strategic Implementation: 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.
• Data Pipeline Mastery: 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.
• Technical Excellence & Mentorship: 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. Mentor and technically guide senior and lead developers.
• SDLC Ownership: 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.
• Cross-Functional Collaboration: 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 that align with business objectives and architectural standards.
• Innovation & Research: 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.

Required Skills and Qualifications

• Senior Data Engineering Expertise: 7+ years of progressive experience in data engineering and software development, with a significant focus on building high-performance, large-scale distributed systems.
• Java Mastery: 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.
• Real-time Streaming Core: Proven, hands-on production experience and deep architectural understanding of:
• Apache Kafka or related technologies: For high-throughput, fault-tolerant message queuing and streaming.
• Apache Flink or related technologies: For advanced real-time stream processing, complex event processing (CEP), and stateful computations.
• Apache Pinot or related technologies: For ultra-low-latency OLAP queries on streaming data.
• Distributed Systems Architecture: Strong expertise in designing and implementing highly available, scalable, and resilient distributed systems.
• Data Storage & Querying: Extensive experience with large-scale data storage solutions (e.g., S3, HDFS) and distributed query engines (e.g., Trino/Presto, Spark SQL).
• SQL Proficiency: Advanced SQL knowledge with experience in optimizing complex queries for large datasets.
• Agile Leadership: Demonstrated experience leading technical initiatives and teams within an Agile software development environment.
• Communication & Problem Solving: Exceptional communication, analytical, and problem-solving skills, with the ability to articulate complex technical concepts to diverse audiences and drive consensus on architectural decisions.

Preferred Skills and Qualifications

• Cloud-Native Data Ecosystems: Experience with cloud-native data services on platforms like AWS, Azure, or GCP, particularly related to streaming and real-time analytics.
• Container Orchestration: Hands-on experience with containerization and orchestration technologies such as Kubernetes and OpenShift for deploying and managing real-time data applications.
• API Development: Experience in designing and implementing high-performance RESTful APIs and event-driven microservices architectures.
• Performance Engineering: Deep understanding and experience with performance tuning, profiling, and optimization of real-time streaming applications and data stores.
• Financial Domain Knowledge: Strong understanding of financial derivatives, fixed income products, and risk management concepts from a technical data perspective.
• Technical Leadership & Mentoring: A proven track record of mentoring junior to senior engineers, fostering technical growth, and building high-performing engineering teams.
• Data Governance & Security: Experience with data governance, data quality, and security best practices in real-time data environments.
• Global Team Experience: Experience working effectively within a geographically distributed, global development team.

Qualification / Education

• Advanced Degree: Strong academic record, ideally with a Master's or Ph.D. in Computer Science, Electrical Engineering, or a related technical/quantitative discipline.
• Architectural Delivery: Demonstrable success in architecting, leading, and delivering complex, multi-tiered, high-performance real-time data applications and platforms.
• Domain Acumen: 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.