Drive the modernization of the trade data capture process by transitioning from batch file transfers to real-time data transfer methods
Implement and optimize data pipelines into a bi-temporal OLTP data store
Integrate AI/ML solutions into data pipelines, complex migrations, and system reconciliation
Design and implement backend services, including RESTful API design and implementation
Architect and configure Apache Kafka for data streaming and event-driven architecture
Lead technical implementation across multiple technology domains including APIs, microservices, event streaming, logging and monitoring, databases, containers, serverless frameworks, and DevOps
Collaborate with team members and stakeholders to ensure successful data modernization initiatives
Qualifications
Required
8–10 years of hands-on experience in application development
8+ years of hands-on experience with languages and frameworks including Java or Python
2–3 years of AI experience
3+ years of backend service development, including RESTful API design and implementation
Practical experience integrating AI/ML solutions into data pipelines, complex migrations, and system reconciliation
Proven hands-on experience with Apache Kafka (installation, configuration, development)
Strong knowledge of data streaming concepts and distributed systems
Experience with CI/CD platforms and related technologies
Hands-on experience with multiple technologies including APIs, microservices, event streaming, logging and monitoring, databases (SQL, NoSQL), containers, serverless frameworks, and DevOps
Bachelor's degree in computer science or equivalent experience
Highly motivated and self-driven professional with strong hands-on technical skills
Strong verbal and written communication skills
Strong partnership, collaboration, and leadership skills
Preferred
Familiarity with cloud platforms (AWS primarily) and containerization (Docker, Kubernetes)
Background in real-time analytics and event-driven architecture
Advanced studies or degree beyond bachelor's level