Job Description & Details
This is a year-long contract gig with a major financial institution through Genesis10, requiring you to sit onsite in either Pennington, NJ or Plano, TX. You will be building resilient, distributed systems that power core financial infrastructure, meaning your code needs to be performant, secure, and ready to handle heavy transaction loads without breaking a sweat.
What You'll Actually Be Doing
You'll be jumping straight into the deep end, bridging the gap between sleek frontend interfaces and heavy-duty backend microservices. Your days will involve spinning up RESTful APIs, wiring up event-driven pipelines using Apache Kafka, and making sure data flows smoothly between distributed nodes and databases like PostgreSQL or MongoDB. You won't just be writing isolated features; you'll own the lifecycle from writing unit tests and pushing through CI/CD pipelines to ensuring enterprise-grade security compliance.
The Core Tech Stack
Java with Spring Boot or Python (FastAPI/Flask/Django) is your bread and butter here for backend logic, and you absolutely must know your way around Apache Kafka for messaging and event streaming. On the user-facing side, expect to touch modern JavaScript frameworks like React, Angular, or Vue. Since this is banking tech, a rock-solid understanding of microservices architecture and distributed systems is non-negotiable if you want to keep up with their scaling demands.
Interview Expectations
Expect the hiring team to grill you on distributed systems resilience, specifically asking how you handle message deduplication and failure recovery in Apache Kafka when consumers go down. They also want to see how you structure clean domain models in Java or Python, so be prepared to whiteboard a scalable microservices architecture under the hood of a high-throughput payment processing system.
Application Advice
Your resume needs to scream reliability and scale. Make sure to explicitly highlight your hands-on production experience with Apache Kafka producers, consumers, and streams alongside your Java or Python microservices work. Drop in specific metrics where you optimized database queries or reduced API latency to make it past the initial automated screening and catch the engineering manager's eye.