Data Engineer

About the Company

Easebuzz is a fintech organization that enables online merchants to accept, process, and disburse payments through developer-friendly APIs. The company focuses on building plug-and-play products including payment infrastructure for lending, subscriptions, and eKYC.

Responsibilities

• Design, develop, and optimize stream processing pipelines using Apache Flink and Kafka
• Implement robust data ingestion pipelines to collect and distribute streaming data
• Perform data transformation and enrichment using Spark Streaming
• Optimize pipelines for performance, scalability, low-latency, and high-throughput
• Monitor stream processing jobs and troubleshoot issues to ensure minimal downtime
• Leverage AWS services like Amazon Kinesis, AWS Lambda, and Amazon EMR
• Implement data governance and security measures to protect sensitive data
• Collaborate with data scientists, software engineers, and business stakeholders
• Create and maintain comprehensive technical documentation

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 2-5 years of professional experience in data engineering with a focus on stream processing
• Strong proficiency in Apache Flink and Kafka
• Hands-on experience with Spark and Spark Streaming
• Solid understanding of AWS services (Kinesis, Lambda, EMR, etc.)
• Proficiency in Java, Scala, or Python
• Strong problem-solving skills for complex distributed systems
• Excellent communication and collaboration skills

Preferred Qualifications

• Experience with containerization and orchestration tools like Docker and Kubernetes