Stream Processing Specialist

6 days ago

Hyderabad, Telangana, India beBeeKafka Full time ₹ 12,00,000 - ₹ 20,10,000
Job Title:

Real-Time Data Processing Engineer

Job Description:

We are seeking a skilled Real-Time Data Processing Engineer to design, develop and maintain real-time streaming pipelines using Apache Kafka. This role will play a pivotal part in enabling scalable, fault-tolerant and governed data streaming across our enterprise systems.

The ideal candidate will have a strong background in backend or data engineering with experience in Apache Kafka. They should be proficient in Java for building Kafka producers/consumers and integration with backend services. Additionally, they should have a deep understanding of Kafka internals and experience with schema management using Confluent Schema Registry, Avro, or Protobuf.

The successful candidate will work closely with DevOps teams to automate CI/CD pipelines, deployment and infrastructure provisioning for Kafka components. They will also be responsible for implementing security best practices, monitoring and troubleshooting Kafka cluster health, latency, throughput and message delivery guarantees.

Requirements:
  • 5-7 years of experience in backend or data engineering with strong focus on Apache Kafka.
  • Proficiency in Java for building Kafka producers/consumers and integration with backend services.
  • Deep understanding of Kafka internals (brokers, partitions, consumer groups, offsets, replication, etc.).
  • Experience with schema management using Confluent Schema Registry, Avro, or Protobuf.
  • Experience with CI/CD pipelines for Kafka component deployment and integration.
  • Strong collaboration skills with DevOps teams to manage Kafka infrastructure, security and automation.
  • Solid understanding of real-time data processing concepts, fault tolerance and data consistency.
Desirable Skills:
  • Experience with Kafka Streams, ksqlDB, or Apache Flink for stream processing.
  • Familiarity with Kafka Connect and connectors for data ingestion and export.
  • Exposure to Confluent Kafka Platform and Kafka REST Proxy.
  • Experience with monitoring and observability tools (e.g., Grafana, ELK Stack).
  • Understanding of container orchestration platforms like Kubernetes or OpenShift.
  • Knowledge of cloud-native Kafka deployments (AWS MSK).
  • Familiarity with Spring Boot for integrating Kafka in microservice environments.

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