We are seeking a skilled Kafka Data Engineer with 3 years of experience in designing, developing, and maintaining distributed streaming platforms. The ideal candidate will have a strong background in working with Apache Kafka, along with proficiency in related technologies such as Scala, Spark, and Hadoop. The role involves building and optimizing real-time data pipelines, integrating Kafka with various data sources, and ensuring the scalability and reliability of our data infrastructure.
Key Responsibilities:
Kafka Infrastructure Development:
Design, implement, and manage Apache Kafka clusters to support real-time data streaming and processing.
Develop custom Kafka producers, consumers, and stream processors to enable real-time data flow across various systems.
Data Pipeline Management:
Build and maintain data pipelines to ensure seamless data ingestion, transformation, and distribution using Kafka and related technologies.
Optimize and monitor data pipelines for performance, scalability, and reliability, ensuring low-latency data processing.
Integration and Implementation:
Integrate Kafka with existing data platforms, such as Hadoop, Spark, and other databases, to enable efficient data processing and storage.
Work closely with development and data engineering teams to implement Kafka-based solutions that meet business needs.
Monitoring and Troubleshooting:
Set up monitoring tools and alerts to ensure the health and performance of Kafka clusters and related data pipelines.
Diagnose and troubleshoot issues related to Kafka, ensuring minimal downtime and data loss.
Performance Tuning and Optimization:
Fine-tune Kafka configurations for optimal performance and resource utilization.
Implement best practices for managing Kafka topics, partitions, and brokers to ensure efficient data streaming.
Security and Compliance:
Implement security measures to protect data in transit and ensure compliance with organizational policies.
Manage access controls and encryption settings for Kafka clusters.
Documentation and Collaboration:
Maintain detailed documentation of Kafka architecture, data flows, and configurations.
Collaborate with cross-functional teams to gather requirements and deliver robust Kafka solutions.
Technical Skills: Core Technologies:
Apache Kafka (Kafka Streams, Kafka Connect).
Scala or Java for developing Kafka applications.
Spark for stream processing.
Hadoop ecosystem for big data integration.
SQL for querying and managing data.
Docker and Kubernetes for containerization and orchestration.
Developer Tools:
Git for version control.
Jenkins or similar CI/CD tools for automated deployments.
Monitoring tools such as Prometheus, Grafana, or Confluent Control Center.
Additional Skills:
Understanding of distributed systems and event-driven architectures.
Experience with message queue systems like RabbitMQ or ActiveMQ.
Familiarity with cloud platforms (AWS, Google Cloud, or Azure) is a plus.
Qualifications:
Bachelor's degree in Computer Science, Information Technology, or a related field.
3 years of hands-on experience in developing and managing Apache Kafka-based solutions.
Proven experience with real-time data streaming and event-driven architectures.
Strong problem-solving skills and the ability to troubleshoot complex data issues.
Excellent communication and collaboration skills to work with cross-functional teams.
Preferred:
Experience in industries such as finance, telecom, or e-commerce where real-time data processing is critical.
Certification in Apache Kafka or related technologies.
Familiarity with microservices architecture.
Apache, Kafka, Scala, Spark, Hadoop, SQL, Docker, Kubernetes, Git, Jenkins, Prometheus.