Associate Staff Engineer (Data Engineer Apache Kafka, Flink, Java)

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.
• Good 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 :

Bachelors or masters degree in computer science Information Technology or a related field.

Remote Work :

No

Employment Type :

Full-time