Java Backend Developer
1 week ago
Role: MongoDB Expert and Lead Developer with Kafka and Java Microservices
• Primary Skills:
- MongoDB (Expert)
- Java Microservices
- Kaka
• Work on MongoDB for framework and other data analytics data ingest from different sources system.
• Query Optimization: Analyze and optimize MongoDB queries for performance efficiency.
• Index Management: Create and manage indexes to improve query performance.
• Collaboration with Developers: Work closely with software developers to integrate MongoDB effectively within applications and to understand and fulfill data storage requirements.
• Code Reviews: Review and provide feedback on database-related code to ensure best practices and efficiency.
• Microservices Architecture Design: Design robust, scalable, and maintainable microservices architectures, ensuring they align with business needs and technical requirements.
• Technology Stack Selection: Choose appropriate technologies, frameworks, and tools for building and managing microservices, focusing on Java-based solutions.
• Integration: Design and implement integration strategies for microservices to communicate effectively with each other and with external systems.
• Sound knowledge in Java Microservices and good hands-on experience for data and analytical platform
• Strong experience in Kafka for data streaming process and data ingestion to the data platform
• Building and setting up the Kafka streaming framework and enabling the data ingestion process to manage the data onboarding seamlessly.
• Extensive experience in database query tuning, performance tuning, and troubleshooting application issues on OLTP/OLAP systems.
• RDBMS Architecture, T-SQL query and Query Optimization knowledge and work experience
• Provide support to team members and helping them to understand the projects and requirements and guiding them to create the optimized solution of it.
• team player and proven track record of working in various team sizes performing cross-functional roles.
• Ensure that their code has high quality by applying techniques like TDD and BDD and meets non-functional requirements like security.
• Collaboration with Development Teams: Work closely with software developers to integrate Kafka into applications and ensure they are using best practices for event streaming.
• Issue Resolution: Troubleshoot and resolve issues related to Kafka clusters, data pipelines, and integrations.
• Performance Tuning: Optimize Kafka settings, such as topic partitioning, replication factors, and log retention policies, for improved performance.
• Monitoring and Alerts: Implement monitoring solutions to track the health and performance of Kafka clusters, using tools like Prometheus, Grafana, or Confluent Control Center.
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