Citi-posted 1 day ago
Full-time • Mid Level
New York, NY
5,001-10,000 employees

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. 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. 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. 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. 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.

  • Serve as the principal architect for scalable, high-performance Java-based real-time data solutions
  • Drive the strategic implementation and optimization of distributed stream processing frameworks (Apache Kafka, Apache Flink) and real-time data storage technologies (Apache Pinot)
  • 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
  • Mentor and technically guide senior and lead developers
  • Drive significant contributions across all phases of the Agile software development lifecycle
  • Collaborate strategically with business analysts, product managers, quality assurance teams, and other engineering leads
  • Stay abreast of industry trends and emerging technologies in real-time data processing, distributed systems, and cloud-native architectures
  • 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
  • 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
  • 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)
  • Advanced SQL knowledge with experience in optimizing complex queries for large datasets
  • Demonstrated experience leading technical initiatives and teams within an Agile software development environment
  • Exceptional communication, analytical, and problem-solving skills, with the ability to articulate complex technical concepts to diverse audiences and drive consensus on architectural decisions
  • Experience with cloud-native data services on platforms like AWS, Azure, or GCP, particularly related to streaming and real-time analytics
  • Hands-on experience with containerization and orchestration technologies such as Kubernetes and OpenShift for deploying and managing real-time data applications
  • Experience in designing and implementing high-performance RESTful APIs and event-driven microservices architectures
  • Deep understanding and experience with performance tuning, profiling, and optimization of real-time streaming applications and data stores
  • Strong understanding of financial derivatives, fixed income products, and risk management concepts from a technical data perspective
  • A proven track record of mentoring junior to senior engineers, fostering technical growth, and building high-performing engineering teams
  • Experience with data governance, data quality, and security best practices in real-time data environments
  • Experience working effectively within a geographically distributed, global development team
  • 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
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