Job Description

Role: Architect MongoDB, Kafka and Java Microservices

Proficiency in MongoDB, understanding of NoSQL databases, familiarity with database design and architecture principles.
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 K afka clusters, using tools like Prometheus, Grafana, or Confluent Control Center.

Thanks & Regards

Ramandeep Kumar