Responsibilities
Design \& Build Streaming Applications
● Design, develop, and operate event\-driven services using Java and Apache Kafka.
● Build real\-time data processing pipelines using Kafka Streams.
● Design scalable topic structures, partitions, and key strategies to ensure
performance, ordering, and reliability.
Kafka Streams \& Stateful Processing
● Develop applications using KStream and KTable abstractions.
● Implement stateful processing, aggregations, joins, and interactive queries.
● Design and manage state stores backed by changelog topics.
● Implement windowing strategies including tumbling, hopping, sliding, and session
windows.
● Handle late\-arriving and out\-of\-order events effectively.
● Manage RocksDB state stores and ensure processing guarantees including
exactly\-once semantics.
Reliability \& Performance
● Monitor and troubleshoot consumer lag, partition skew, and rebalancing issues.
● Improve system fault tolerance through analysis of logs, metrics, offsets, and
consumer group behavior.
● Optimize serialization and schema management using Avro, JSON, and Schema
Registry solutions.
● Enhance application performance, scalability, and throughput for high\-volume
streaming workloads.
Collaboration \& Code Quality
● Write clean, maintainable, and well\-tested Java code.
● Conduct code reviews and mentor junior developers.
● Promote best practices in Kafka architecture and streaming design patterns.
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● Collaborate with architects, product managers, DevOps engineers, and platform
teams to deliver production\-ready solutions.
Requirements \& Qualifications
Core Technical Skills
● 6–10 years of hands\-on experience in software development with a strong focus on
Java\-based applications.
● Extensive expertise in Java development, including multithreading, concurrency,
collections framework, memory management, and JVM performance optimization.
● Deep understanding of Apache Kafka Core components, including Producers,
Consumers, Brokers, Topics, Partitions, Offsets, and Consumer Groups.
● Strong hands\-on experience with Kafka Streams, including KStream, KTable,
GlobalKTable, stream processing, joins, aggregations, and interactive queries.
● Solid understanding of event\-driven architecture and stream\-processing concepts,
including event\-time and processing\-time semantics.
● Experience implementing advanced windowing strategies such as Tumbling,
Hopping, Sliding, and Session Windows.
● Proficiency in developing microservices and event\-driven applications using Spring
Boot and Spring Kafka.
● Experience with schema management and serialization frameworks using Avro,
JSON, and Schema Registry solutions.
● Strong analytical thinking, troubleshooting, debugging, and performance
optimization skills.
● Proven ability to identify, diagnose, and resolve complex issues in distributed
systems and streaming applications.
● Experience working in Agile/Scrum environments with active participation in sprint
planning, code reviews, and continuous delivery practices.
● Strong understanding of software engineering best practices, clean code principles,
design patterns, and scalable application architecture.
Pay: ₹549,658\.55 \- ₹1,915,392\.86 per year
Work Location: In person
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