Requirements JAVA, spring Boot, Restful, DS Algo, Experience in building, optimizing, and maintaining large data pipelines , building distributed data services and solutions.
Development, Testing, and deployment experience with GitHub, Docker/Kubernetes
Job Description:
- Strong expertise in Java and the Spring Framework, particularly Spring Boot.
- Good understanding of SQL oracle, SQL server or similar languages.
- Core Engineering: Data structures & algorithms, testing (Junit etc), Git, clean code.
- Experience with graph databases (e.g., Neo4j, JanusGraph) and graph query languages.
- Ops & CI/CD: Monitoring (Prometheus/Grafana), logging, pipelines (Jenkins/GitHub Actions).
- Cloud Native: Docker, Kubernetes (deploy, network, scale, troubleshoot).
- 6+ years of directly applicable experience
- BS in Computer Science, Engineering, or equivalent experience.
About the team
Our Cloud Data Technologies team oversees data infrastructure and the management of the end-to-end data lifecycle.
Project and role
As a Software Engineer on our team, you will work on our Hadoop-based data warehouse and cloud development environment, contributing to scalable and reliable big data solutions and services for analytics and business insights. This is a hands-on role focused on building, optimizing, and maintaining large data pipelines , building distributed data services and solutions.
Key Responsibilities
- Design, develop, and maintain robust data solutions and services and related Hadoop ecosystems, ensuring data reliability, scalability, and performance.
- Optimize and troubleshoot distributed systems for ingestion, storage, and processing.
- Collaborate with data engineers, analysts, and platform engineers to align solutions with business needs.
- Ensure data security, integrity, and compliance throughout the infrastructure.
- Maintain documentation and contribute to architecture reviews.
- Participate in incident response and operational excellence initiatives for the data warehouse.
- Continuously learn and apply new Hadoop ecosystem tools and data technologies.
