Data engineer with Kubernetes and AWS

Data engineer - Kubernetes & AWSHybrid - 2daysWorksite Address: 9509 Key West Ave Fl 2,Rockville,Maryland,United States,20850-3329 Top Skills Details 1. Kubernetes (EKS) in AWS Environments- Maintaining and operating production clusters, diagnosing scaling, networking, and workload stability issues2. AWS Cloud infrastructure- AWS services fundamentals- EKS specific AWS integrations3. Big Data Engineering exposure- Petabyte-scale data processing- Spark/Hadoop4. Python, SQL, Scala5. CI/CD Responsibilities: Design, develop, and maintain large-scale data processing pipelines using Big Data technologies (e.g., Hadoop, Spark, Python, Scala). Architect and deploy containerized big data workloads on Amazon EMR on EKS (Elastic Kubernetes Service). Design and implement Kubernetes-based infrastructure for running Spark applications at scale. Implement data ingestion, storage, transformation, and analysis solutions that are scalable, efficient, and reliable. Stay current with industry trends and emerging Big Data technologies to continuously improve the data architecture. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Optimize and enhance existing data pipelines for performance, scalability, and reliability. Develop automated testing frameworks and implement continuous testing for data quality assurance. Conduct unit, integration, and system testing to ensure the robustness and accuracy of data pipelines. Work with data scientists and analysts to support data-driven decision-making across the organization. Ability to write and maintain automated unit, integration, and end-to-end tests. Monitor and troubleshoot data pipelines in production environments to identify and resolve issues. Manage Kubernetes clusters, pods, services, and deployments for big data workloads.