Kafka Data Engineer- Bangalore- Electronic City- Hybrid

1 week ago

Bengaluru, Karnataka, India ORION SYSTEMS Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Job Description- Kafka Data Engineer

Role Overview:

We are seeking a skilled Kafka Data Engineer to design, build, and optimize real-time data streaming solutions using Apache Kafka and Google Cloud Platform (GCP). The ideal candidate will have hands-on experience in Kafka topic design, data pipeline development, and cloud-native data engineering practices.

Key Responsibilities:

  • Design and implement scalable and secure Kafka-based data streaming solutions.

  • Develop and maintain real-time and batch data pipelines using GCP services such as Dataflow, Pub/Sub, and Big Query.

  • Collaborate with architects, data engineers, and DevOps teams to ensure seamless integration of Kafka with cloud data platforms.

  • Optimize Kafka topic design, partitioning strategies, and message schemas for performance and reliability.

  • Monitor and troubleshoot Kafka clusters and streaming jobs to ensure high availability and low latency.

  • Implement best practices for data quality, governance, and security in streaming environments.

  • Participate in code reviews, design discussions, and continuous improvement initiatives.

Required Qualifications:

  • 5+ years of experience in data engineering with a focus on real-time data processing.

  • Strong hands-on experience with Apache Kafka, including topic design, schema registry, and Kafka Streams.

  • Proficiency in GCP services such as Pub/Sub, Dataflow, BigQuery, and Cloud Storage.

  • Solid understanding of ETL/ELT processes, data modeling, and distributed systems.

  • Experience with CI/CD pipelines and infrastructure-as-code tools like Terraform.

  • Strong problem-solving skills and the ability to work in a collaborative, agile environment.

Preferred Qualifications:

  • GCP certifications (e.g., Professional Data Engineer).

  • Experience with DevOps practices and containerization (Docker, Kubernetes).

  • Familiarity with multi-cloud environments and hybrid data architectures.

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