Data Engineer - Kafka

As a Data Engineer with Kafka Experience, your role will involve building end-to-end data pipelines, including data ingestion, ETL/ELT, SQL, NRT/batch processing, data models, and Lakehouse. You should have a strong understanding of messaging systems, event-driven architectures, and real-time data processing. Your hands-on development experience in Confluent Kafka should cover topics, partitions, producers, consumers, and Kafka Streams. It is important to have working experience with Schema Registry, KSQLDB, and Kafka Connect, especially in sourcing/sinking data to databases. Your ability to troubleshoot operational ETL jobs, conduct root cause analysis, and resolve issues in a real-time environment will be crucial. An understanding of Cloud technologies and CI/CD/DevOps practices is essential for this role. Exposure to Snowflake Data Cloud would be considered a plus. **Key Responsibilities:** - Build end-to-end data pipelines - Work with messaging systems and event-driven architectures - Develop in Confluent Kafka including topics, partitions, producers, consumers, and Kafka Streams - Utilize Schema Registry, KSQLDB, and Kafka Connect for data operations - Troubleshoot operational ETL jobs and resolve issues in real-time - Implement Cloud technologies and CI/CD/DevOps practices - Source/sink data to databases using Kafka Connect **Qualifications Required:** - Strong experience in building data pipelines - Knowledge of messaging systems and event-driven architectures - Hands-on development experience in Confluent Kafka - Working experience with Schema Registry, KSQLDB, and Kafka Connect - Ability to troubleshoot operational ETL jobs - Understanding of Cloud technologies and CI/CD/DevOps practices - Exposure to Snowflake Data Cloud is a plus As a Data Engineer with Kafka Experience, your role will involve building end-to-end data pipelines, including data ingestion, ETL/ELT, SQL, NRT/batch processing, data models, and Lakehouse. You should have a strong understanding of messaging systems, event-driven architectures, and real-time data processing. Your hands-on development experience in Confluent Kafka should cover topics, partitions, producers, consumers, and Kafka Streams. It is important to have working experience with Schema Registry, KSQLDB, and Kafka Connect, especially in sourcing/sinking data to databases. Your ability to troubleshoot operational ETL jobs, conduct root cause analysis, and resolve issues in a real-time environment will be crucial. An understanding of Cloud technologies and CI/CD/DevOps practices is essential for this role. Exposure to Snowflake Data Cloud would be considered a plus. **Key Responsibilities:** - Build end-to-end data pipelines - Work with messaging systems and event-driven architectures - Develop in Confluent Kafka including topics, partitions, producers, consumers, and Kafka Streams - Utilize Schema Registry, KSQLDB, and Kafka Connect for data operations - Troubleshoot operational ETL jobs and resolve issues in real-time - Implement Cloud technologies and CI/CD/DevOps practices - Source/sink data to databases using Kafka Connect **Qualifications Required:** - Strong experience in building data pipelines - Knowledge of messaging systems and event-driven architectures - Hands-on development experience in Confluent Kafka - Working experience with Schema Registry, KSQLDB, and Kafka Connect - Ability to troubleshoot operational ETL jobs - Understanding of Cloud technologies and CI/CD/DevOps practices - Exposure to Snowflake Data Cloud is a plus