Description

Key Skills: AWS, Data Engineer, Kubernetes, Containerization (Docker, Kubernetes), Data Warehouse

Roles and Responsibilities:

• Design, develop, integrate, and implement scalable data warehouses, data marts, and cloud-based data engineering solutions on AWS.
• Design and implement robust data pipelines for batch processing, real-time data ingestion, and stream processing.
• Develop event-driven architectures using AWS services, Apache Kafka, Amazon Kinesis, and AWS Lambda.
• Configure, deploy, and manage AWS services related to databases, networking, security, storage, and data processing.
• Develop and optimize data warehouse solutions using Amazon Redshift, AWS Glue, Amazon RDS, and other relevant AWS services.
• Implement and manage infrastructure provisioning and configuration automation using Terraform, AWS CloudFormation, and tools such as Ansible, Puppet, or Chef.
• Build and maintain CI/CD pipelines using AWS CodeCommit, CodeBuild, CodeDeploy, CodePipeline, Jenkins, GitHub, and GitLab CI.
• Design and implement containerized applications and data services using Docker and Kubernetes.
• Build, configure, and manage Kubernetes-based container hosting platforms, including deployment, scaling, and orchestration.
• Configure and manage AWS services such as API Gateway, Elastic Load Balancing, Auto Scaling, and Amazon CloudWatch.
• Implement monitoring, logging, security, and performance optimization practices for cloud infrastructure and data pipelines.
• Design and maintain complex CI/CD workflows using Jenkinsfiles, GitLab CI, Spinnaker, AWS CodeDeploy, and Docker containers.
• Collaborate with cross-functional teams to deliver reliable, scalable, and secure cloud data solutions.
• Participate in Agile, Scrum, or SAFe development processes, including sprint planning, daily stand-ups, and retrospectives.

Skills Required:

• Strong experience in data engineering, data warehousing, data mart development, and application development on AWS.
• Hands-on experience with AWS services, particularly Amazon Redshift, AWS Glue, Amazon Kinesis, AWS Lambda, Amazon RDS, and AWS Data Pipeline or equivalent orchestration solutions.
• Experience developing big data and stream-processing platforms using Apache Kafka and other real-time data technologies.
• Strong understanding of event-driven architecture and real-time data ingestion strategies.
• Experience with Infrastructure as Code (IaC) and automated cloud resource provisioning using Terraform and AWS CloudFormation.
• Knowledge of configuration management and automation tools such as Ansible, Puppet, or Chef.
• Hands-on experience with CI/CD tools, including Jenkins, GitHub, GitLab CI, and AWS developer tools.
• Practical experience with Docker containerization and Kubernetes orchestration.
• Understanding of cloud networking, security, load balancing, auto-scaling, monitoring, and logging.
• Strong problem-solving, analytical, communication, and collaboration skills.
• Experience working in Agile, Scrum, or SAFe environments.

Education: Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.

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  • A master's degree or relevant technical certifications is an added advantage.
  • AWS certifications in Data Engineering, Solutions Architecture, or Cloud Operations are desirable

Key Skills

Education

Any Graduate