Senior Java Backend Developer

Mandatory Skills Java, MongoDB Preferred Skill Eclipse Vert.x Primary Focus Backend development, large-volume data processing, and performance engineering Mandatory Technical Skills

Java “ 8 years of relevant software development experience, including substantial hands-on Java backend development. “ Strong knowledge of Core Java and object-oriented programming principles. “ Strong understanding of collections, multithreading, concurrency, exception handling, memory management, JVM fundamentals, and performance Eligible to workimization. “ Experience developing enterprise-grade backend services and APIs. “ Proven ability to investigate and resolve Java application performance problems. MongoDB “ Strong hands-on development experience with MongoDB as a primary backend database. “ Strong understanding of MongoDB document modeling, queries, indexes, aggregation pipelines, query Eligible to workimization, and performance analysis. “ Experience working with large MongoDB datasets and high-volume data processing. “ Ability to diagnose slow queries and inefficient data-access patterns and implement appropriate Eligible to workimizations.

Preferred / Nice-to-Have Skills “ Hands-on experience with Eclipse Vert.x. “ Understanding of asynchronous, reactive, and event-driven backend development. “ Experience developing high-throughput or highly concurrent services using Vert.x. “ Experience with RESTful APIs, microservices, distributed systems, and asynchronous processing. “ Exposure to application profiling, observability, monitoring, and production-support tools. “ Experience with Git, CI/CD, automated deployment practices, and containerized environments.

Performance Engineering Expectations A critical aspect of this role is supporting performance-sensitive applications that process large amounts of data. The developer must be comfortable investigating issues across both the Java application and MongoDB database layers. The candidate should be able to determine whether degraded performance is caused by inefficient MongoDB queries or aggregations, inappropriate indexing, excessive data retrieval, Java memory or garbage-collection pressure, thread contention, concurrency behavior, or inefficient application logic, and then implement and validate an appropriate corrective solution.