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
Benefits:
- Health insurance
- Provident Fund
Application Question(s):
Experience:
- Kafka: 6 years (Required)
Work Location: In person
