A technology services company is looking for a Mid-Senior level Java Software Engineer to design and maintain scalable microservices. The role involves building data pipelines, deploying services in Docker/Kubernetes environments, and integrating applications in AWS. Proficiency in Java, Spring Boot, and Kafka is essential. This contract position offers opportunities to work in a dynamic environment focused on high-quality code and innovative solutions.
Qualifications
Strong programming skills in Java and experience with Spring Boot.
Hands-on experience with Microservices architecture and RESTful APIs.
Proficiency with Kafka and distributed streaming systems.
Responsibilities
Design, develop, and maintain scalable microservices using Java.
Build and optimize real-time data pipelines using Apache Kafka.
Deploy, manage, and monitor services in containerized environments.
Skills
Programming skills in Java
Experience with Spring Boot
Microservices architecture
RESTful APIs
Proficiency with Kafka
SQL and data modeling
Containerization (Docker)
Orchestration (Kubernetes)
Data processing (Flink, Spark, Databricks)
Familiarity with AWS services
Tools
Docker
Kubernetes
AWS
Datadog
Job description
Java Software Engineer
Responsibilities
Design, develop, and maintain scalable microservices using Java and Spring Boot.
Build and optimize real-time data pipelines leveraging Apache Kafka, Flink, and Spark/Databricks.
Develop robust data distribution and streaming solutions for high-throughput systems.
Deploy, manage, and monitor services in containerized environments (Docker/Kubernetes).
Write efficient and optimized SQL queries for relational databases.
Integrate and manage applications in AWS cloud environments.
Collaborate with cross‑functional teams to ensure smooth delivery and integration of features.
Implement monitoring and observability solutions (e.g., Datadog) for system health and performance tracking.
Maintain high standards of code quality, reliability, and security.
Primary Skills
Strong programming skills in Java and Spring Boot.
Hands‑on experience with Microservices architecture and RESTful APIs.
Proficiency with Kafka and distributed streaming systems.
Solid understanding of SQL and data modeling.
Experience with containerization (Docker) and orchestration (Kubernetes).
Working knowledge of Flink, Spark, or Databricks for data processing.
Familiarity with AWS services (ECS, EKS, S3, Lambda, etc.).
Basic scripting in Python for automation or data manipulation.
Secondary Skills
Experience with Datadog, Prometheus, or other monitoring tools.
Exposure to CI/CD pipelines and DevOps practices.
Knowledge of data engineering best practices and real‑time analytics.