Job Description

Requirements

- Minimum 4+ years of experience in Data Engineering with a focus on real-time data processing and streaming technologies.
- Strong hands-on experience in Java development and building enterprise-grade applications.
- Expertise in Apache Kafka, including Producers, Consumers, Topics, Partitions, Consumer Groups, Kafka Connect, and event-driven architectures.
- Hands-on experience with Apache Flink for real-time stream processing, stateful computations, windowing, and fault-tolerant data pipelines.
- Experience designing, developing, and deploying scalable real-time streaming data pipelines.
- Solid understanding of distributed systems, messaging patterns, and high-throughput, low-latency data processing.
- Experience working with REST APIs, microservices, and integration frameworks.
- Valuable understanding of data ingestion, transformation, and processing techniques in streaming environments.
- Familiarity with real-time analytics and event-driven architectures.
- Experience working in Banking, Financial Services, or other mission-critical environments is preferred.
- Good understanding of containerization and cloud platforms is an added advantage.
- Strong analytical, problem-solving, and debugging skills.
- Excellent communication and stakeholder management skills.

Responsibilities





- Design, develop, and maintain scalable real-time data pipelines using Apache Kafka, Java, and Apache Flink.
- Build and optimize low-latency, high-throughput streaming solutions for business-critical data processing needs.
- Develop event-driven applications and data workflows to support real-time analytics and operational reporting.
- Collaborate with architects, platform teams, and business stakeholders to understand data requirements and implement effective solutions.
- Monitor, troubleshoot, and enhance streaming applications to ensure reliability, scalability, and performance.
- Implement best practices for data quality, security, governance, and operational excellence.
- Optimize Kafka and Flink applications for performance, resilience, and fault tolerance.
- Participate in code reviews, design discussions, and technical solutioning activities.
- Support production deployments and resolve issues related to streaming data platforms.
- Contribute to continuous improvement initiatives by evaluating and adopting modern real-time data engineering practices and technologies.

Qualifications

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

📌 Associate Staff Engineer (Data Engineer -Apache Kafka, Flink, Java) (India)
🏢 Nagarro
📍 India