Job Responsibilities

• Design and develop robust, scalable data pipelines and streaming applications using Java and Apache Kafka, forming the backbone of real-time execution and market data flows.
• Integrate with the cloud by implementing and managing data solutions on AWS, including services such as S3, Lambda, EC2, RDS, and Glue.
• Process data at scale by developing ETL processes for both batch and real-time data ingestion, transformation, and storage.
• Optimize performance by monitoring, troubleshooting, and tuning data flows to ensure reliability and efficiency in a low-latency environment.
• Collaborate cross-functionally with data scientists, analysts, and fellow engineers to understand requirements and deliver production-grade solutions.
• Document thoroughly, maintaining clear records of data flows, architecture, and operational procedures.
• Uphold security and compliance, ensuring all data solutions adhere to the firm's security, privacy, and regulatory standards.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data platform and design analysis and technical documentation, validating outputs and handling data according to sensitivity and security requirements.
• Applies reuse-first, AI-assisted practices within delivery and operational routines (e.g., validation automation and access control review support), ensuring traceability/auditability and alignment to resiliency and security expectations.

 

Required Qualifications, Capabilities, and Skills

Candidates should hold a Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related technical field, and bring experience in data engineering and software development roles. The role demands strong proficiency in Java (core and advanced concepts), hands-on experience with Apache Kafka (producers, consumers, and stream processing), and a solid working knowledge of AWS cloud services including S3, Lambda, EC2, RDS, and Glue. Proficiency in Python is also required.

Beyond core languages and platforms, the ideal candidate will have practical experience with the following:

• ETL tools and data pipeline frameworks
• SQL and NoSQL databases
• Data modelling, data warehousing, and big data technologies
• CI/CD practices and version control (e.g., Git)
• Strong problem-solving and analytical skills, together with excellent communication and teamwork abilities, are essential for success in this collaborative, high-stakes environment.

 

Preferred Qualifications, Capabilities, and Skills

The following experience would distinguish a candidate, though it is not required:

• Containerization technologies (Docker, Kubernetes)
• Exposure to additional programming languages (Scala)
• Data governance and data quality best practices
• AWS certification or related credentials
• Electronic trading and market data feeds
• Familiarity with the Equities trading stack and Futures & Options market structure
• Trading data or FIX-adjacent data pipelines
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.

The Futures & Options Execution Technology team within Equities Technology runs the trading technology stack for the #1 ranked FCM and supports other JPMorganChase lines of business, and is undertaking a multi-year program to modernize core execution platforms. As a Senior lead Software Engineer, you will design, build, and maintain scalable data pipelines and real-time streaming solutionsusing Java, AWS, and Apache Kafkathat power execution, connectivity, and market data across global markets. Leveraging cloud technologies and distributed systems, you will deliver reliable, low-latency data solutions and collaborate with cross-functional teams to drive business insights and operational efficiency.