Architect

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.