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Agivant Technologies India Private Limited

Backend Engineer (Data Infrastructure)

Posted Yesterday
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In-Office
Hyderabad, Telangana, IND
Entry level
In-Office
Hyderabad, Telangana, IND
Entry level
Build and optimize backend systems for real-time and historical data querying. Responsibilities include developing query language runtimes, parsing, semantic analysis, query planning, execution, Kafka-native streaming pipelines, Spring Boot services, and high-performance Java and C++ components. Collaborate on database infrastructure, query optimization, language semantics, type systems, code reviews, and engineering standards.
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About the role:

We are looking for a Backend Engineer to join our core platform team. This is a deep technical role sitting at the intersection of streaming data systems, query engine design, and language implementation. You will build and evolve the systems that allow users to express complex queries over real-time and historical data — from parser to execution. If you have built compilers, database engines, or Kafka-native systems from the ground up, this role was written for you.

Key Responsibilities: 


       Design and implement components of our query language runtime — including parsing, semantic analysis, query planning, and execution.

       Build and extend Kafka-native data pipelines and streaming query execution using Kafka Streams and the broader Kafka ecosystem.

       Develop and maintain backend services and integration layers using Spring Boot.

       Collaborate with database and infrastructure teams to optimize query execution over large-scale storage systems.

       Contribute to the design of language semantics, type systems, and query optimization strategies.

       Write high-performance Java and C++ code; own critical, latency-sensitive system components.

       Review designs and code across the team; set standards for correctness, performance, and maintainability.



Requirements
Required Qualification:

       Proficiency in both Java and C++ — able to write, review, and own production code in either language.

       Strong Kafka knowledge — required at the following levels of depth:

       Ideal Candidate:  Proven experience contributing to the Kafka ecosystem — open-source contributions, Kafka Improvement Proposals (KIPs), or deep architectural work within the Kafka internals (broker, consumer group protocol, log compaction, etc.).

        Minimum Qualification:  Proven hands-on experience building Kafka connectors and stream-processing applications using Kafka Streams in production environments.

       Solid Spring Boot experience — building production-grade backend services, REST/gRPC layers, and integration components.



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