Sr. Data Engineer - (RealTime Streaming)

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 & TechnologiesMandatory 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.