Data Engineer

2 months ago

bangalore, India gethyr Full time

We are seeking a talented and motivated Data Engineer stream processing, particularly utilizing Flink and Kafka, alongside expertise in Spark and AWS technologies.

As a Data Engineer, you will play a crucial role in designing, implementing, and maintaining robust stream processing solutions to handle large volumes of data in real-time, ensuring high performance, scalability, and reliability.

Responsibilities :

  • Stream Processing Development: Design, develop, and optimize stream processing pipelines using Apache Flink and Kafka to process real-time data streams efficiently.
  • Data Ingestion: Implement robust data ingestion pipelines to collect, process, and distribute streaming data from various sources into the Flink and Kafka ecosystems.
  • Data Transformation: Perform data transformation and enrichment operations on streaming data using Spark Streaming and other relevant technologies to derive actionable insights.
  • Performance Optimization: Continuously optimize stream processing pipelines for performance, scalability, and reliability, ensuring low-latency and high-throughput data processing.
  • Monitoring and Troubleshooting: Monitor stream processing jobs, troubleshoot issues, and implement necessary optimizations to ensure smooth operation and minimal downtime.
  • Integration with AWS Services: Leverage AWS technologies such as Amazon Kinesis, AWS Lambda, Amazon EMR, and others to build end-to-end stream processing solutions in the cloud environment.
  • Data Governance and Security: Implement data governance and security measures to ensure compliance with regulatory requirements and protect sensitive data in streaming pipelines.
  • Collaboration: Collaborate closely with cross-functional teams including data scientists, software engineers, and business stakeholders to understand requirements and deliver impactful solutions.
  • Documentation: Create and maintain comprehensive documentation for stream processing pipelines, including design specifications, deployment instructions, and operational procedures.
  • Continuous Learning: Stay updated with the latest advancements in stream processing technologies, tools, and best practices, and incorporate them into the development process as or Master's degree in Computer Science, Engineering, or a related field.
  • 2-5 years of professional experience in data engineering roles with a focus on stream processing.
  • Strong proficiency in Apache Flink and Kafka for building real-time stream processing applications.
  • Hands-on experience with Spark and Spark Streaming for batch and stream processing.
  • Solid understanding of cloud computing platforms, particularly AWS services such as Amazon, Kinesis, AWS Lambda, Amazon EMR, etc.
  • Proficiency in programming languages such as Java, Scala, or Python.
  • Experience with containerization and orchestration tools like Docker and Kubernetes is a plus.
  • Excellent problem-solving skills and the ability to troubleshoot complex distributed systems.
  • Strong communication skills and the ability to work effectively in a collaborative team (ref:hirist.tech)

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