VP Backend Engineer — Scalable Java Microservices

Goldman Sachs; Dallas (WV); On-site; USD 140,000 - 210,000; Full time

Job summary

GOLDMAN SACHS is seeking a Senior Backend Engineer to design, develop, and maintain scalable microservices using Java, Spring Boot, and Spring Batch. You will apply domain-driven design for service isolation and build robust APIs with strong security.

In this role, you will develop real-time data pipelines with Kafka, optimize for low latency, and ensure reliable, scalable data processing across distributed systems.

Qualifications

• 7+ years of backend software engineering experience.
• Deep understanding of Java (8+) and core Spring concepts.
• Expert in Spring Boot and Spring Batch.
• Proven track record building production-grade ETL pipelines.
• Hands-on experience with Kafka or other message brokers.
• Relational databases knowledge and complex SQL.
• Security practices and OWASP awareness.
• Familiarity with CI/CD pipelines (Jenkins/GitLab).

Responsibilities

• Design, develop, and implement scalable microservices with Java and Spring Boot.
• Apply domain-driven design to ensure service isolation and maintainability.
• Optimize application performance for low latency and high throughput.
• Architect and maintain ETL/ELT workflows using Spring Batch.
• Develop RESTful APIs and ensure security with Spring Security, OAuth2, and JWT.
• Build event-driven architectures using Kafka or RabbitMQ.
• Perform database performance tuning and complex SQL for analytics.

Skills

Backend engineering

Java 8+

Spring Framework

Spring Boot

Spring Batch

ETL pipelines

Kafka

SQL/Relational DB

Security practices

Docker

Kubernetes

CI/CD

Tools

Docker

Kubernetes

Jenkins

GitLab

Job description

GOLDMAN SACHS is seeking a Senior Backend Engineer to design, develop, and maintain scalable microservices using Java, Spring Boot, and Spring Batch. You will apply domain-driven design for service isolation and build robust APIs with strong security.

In this role, you will develop real-time data pipelines with Kafka, optimize for low latency, and ensure reliable, scalable data processing across distributed systems.