Data Streaming Engineer (Kafka Confluent & Flink)

About the Role

Data Streaming Engineer

Key Responsibilities

• Design, develop, and maintain real-time streaming applications using Kafka Confluent and Apache Flink.
• Build end-to-end streaming architectures with a focus on scalability, reliability, and low latency.
• Manage Kafka clusters, including topics, partitions, and connectors.
• Optimize Flink jobs for high performance, fault tolerance, and throughput.
• Integrate streaming pipelines with downstream systems such as data lakes, warehouses, and microservices.
• Monitor and troubleshoot streaming workflows to ensure high availability.
• Work closely with data engineering, DevOps, and product teams to deliver robust streaming solutions.

Required Skills & Experience

• 5+ years of experience in data engineering or data streaming roles.
• Strong expertise in the Kafka Confluent Platform, including Connect, Schema Registry, and KSQL.
• Proven experience with Apache Flink (streaming and batch).
• Strong understanding of distributed systems and event-driven architectures.
• Experience building and scaling streaming ETL pipelines.
• Proficiency in Java, Scala, or Python for developing Flink applications.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) is a strong plus.
• Good understanding of CI/CD, Docker, Kubernetes, and monitoring tools.

Nice to Have

• Experience with other messaging systems such as Apache Pulsar, RabbitMQ, or AWS MSK.
• Familiarity with Snowflake, BigQuery, Redshift, or other cloud data warehouses.
• Understanding of microservices-based architectures and API integrations.