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 & 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.