Lead Data Engineer
Posted Updated 9
views
Summary
Designs and builds Spark/Scala pipelines to process large datasets, integrates Elasticsearch for querying, and deploys solutions on OpenShift. Optimizes performance, collaborates with DevOps, and ensures pipeline reliability.
- Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data.
- Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data.
- Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch.
- Collaborate with data engineers, data scientists, and other stakeholders to understand requirements and translate them into technical specifications and solutions.
- Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques.
- Optimize data engineering workflows for containerized deployment and efficient resource utilization.
- Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability.
- Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements.
- Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure.