Senior Java & Data Engineer, AWS / Databricks

The role will focus primarily on developing Java/Spring Boot REST APIs and Python-based ETL/data pipelines using Databricks, deployed on AWS. The ideal candidate will have strong backend engineering and data-processing experience, with a solid understanding of cloud-native development, containerization, microservices, and modern engineering practices.

Title: Senior Java & Data Engineer AWS / Databricks
Location: Wilmington, DE (Onsite)
Duration: 6+ Months of Contract

Must Have:
Java, Spring Boot, REST APIs (40% weightage)
Strong Python and ETL development (60% weightage)
Strong understanding of microservices and API-driven architectures
Docker and Kubernetes
Data Engineering - Databricks
Unit Testing, Integration Testing and API Testing
Bitbucket and CI/CD
Strong debugging, problem-solving, and software engineering fundamentals

Role Description:
We are looking for a hands-on Senior Java & Data Engineer to support a large-scale application modernization and cloud migration initiative.
The role will focus primarily on developing Java/Spring Boot REST APIs and Python-based ETL/data pipelines using Databricks, deployed on AWS.
The ideal candidate will have strong backend engineering and data-processing experience, with a solid understanding of cloud-native development, containerization, microservices, and modern engineering practices.

Responsibilities:
Design, develop, and maintain scalable REST APIs and backend services using Java and Spring Boot.
Develop modular, reusable services following microservices and API-first architecture principles.
Build and maintain Python-based ETL and data-processing pipelines in Databricks.
Implement data ingestion, transformation, validation, reconciliation, and error-handling processes.
Integrate backend services with Databricks, AWS services, and other enterprise systems/data sources.
Containerize applications using Docker and deploy/manage workloads using Kubernetes.
Develop unit and integration tests and ensure high standards for code quality, security, performance, and maintainability.
Participate in solution design, code reviews, troubleshooting, performance optimization, and technical documentation.
Collaborate with architects, frontend developers, data engineers, DevOps teams, and other stakeholders throughout the development lifecycle.
Support CI/CD, automated deployments, monitoring, logging, and production readiness for cloud-native components.
Contribute to modernization by translating legacy capabilities into scalable API-driven and cloud-native solutions.
Leverage modern AI-assisted development approaches where applicable to improve engineering productivity and automation.