Sr. Data Engineer - (RealTime Streaming)

About this role

We are looking for an experienced Senior Data Engineer with strong expertise in real-time streaming technologies and large-scale data engineering solutions. The ideal candidate will have hands-on experience designing, building, and managing highly scalable and fault-tolerant streaming data platforms using Kafka, Flink, Java, and PySpark. The candidate will be responsible for developing high-throughput, low-latency data pipelines, managing Kafka clusters, implementing cloud-native data solutions, and ensuring system reliability, security, and scalability in enterprise environments. Requirements Key Responsibilities Design, develop, implement, and manage Kafka-based real-time streaming architectures capable of handling high-volume and low-latency workloads. Build and maintain scalable streaming data pipelines using Kafka ecosystem components, including: Kafka Connect ksqlDB Schema Registry Develop and optimize real-time data processing applications using: Apache Flink Java PySpark Perform Kafka cluster setup, administration, configuration, tuning, monitoring, and performance optimization. Ensure Kafka clusters are highly available and implement disaster recovery strategies and best practices. Design and implement fault-tolerant, scalable, and resilient streaming systems for enterprise-grade applications. Work with cloud-native applications and modern data engineering frameworks to build scalable solutions. Automate infrastructure provisioning and deployment using Infrastructure-as-Code (IaC) tools such as Terraform. Implement and follow GitOps practices for deployment automation and infrastructure management. Apply robust security standards and best practices, including: SSL / mTLS SASL authentication ACL management Collaborate with cross-functional teams to deliver real-time data engineering solutions aligned with business and analytics requirements. Required Skills & Technologies Mandatory Skills Apache Kafka Apache Flink Java PySpark Real-Time Streaming Architecture Kafka Cluster Management Kafka Connect ksqlDB Schema Registry Streaming Data Pipelines Cloud-Native Applications Terraform Infrastructure-as-Code (IaC) GitOps High Availability & Disaster Recovery Performance Tuning & Optimization Fault Tolerance & Scalability SSL / mTLS SASL ACLs Preferred Experience Strong experience in building enterprise-grade real-time data platforms. Hands-on experience working in high-throughput and low-latency environments. Experience with large-scale distributed data processing systems. Exposure to cloud platforms and modern DevOps practices will be an added advantage.