Cloud Labs Engineer

DataVidhya is building a hands-on learning and interview preparation platform for Data Engineers. We are looking for an experienced Cloud Labs Engineer who can design, build, automate, and maintain practical cloud labs across AWS, Azure, and GCP. These will not be simple tutorial documents. Learners should be able to launch a lab, receive temporary cloud resources, complete practical data engineering tasks, validate their work, and automatically clean up the resources after the session. What You Will Build You will help us create browser-based cloud labs covering use cases such as: - Building data pipelines on AWS, Azure, and GCP - Working with cloud storage, data warehouses, Spark, orchestration, and streaming services - Provisioning temporary cloud environments for individual learners - Automatically validating whether a learner completed the task correctly - Automatically deleting resources after lab completion or timeout - Tracking lab usage, progress, failures, and cloud costs Example Labs Examples of the labs you may build include: AWS - Uploading and processing files using Amazon S3 - Building ETL pipelines with AWS Glue - Running Spark jobs using EMR or EMR Serverless - Querying data using Athena - Loading data into Amazon Redshift - Triggering pipelines using Lambda and EventBridge - Building orchestration workflows using Apache Airflow You are a strong fit if you: - Have previously built cloud sandboxes, training labs, developer environments, or internal cloud platforms - Understand both cloud infrastructure and data engineering - Can make practical architecture decisions based on security, cost, and scalability - Write clean, maintainable automation code - Can independently take a lab from requirements to production - Communicate clearly and document your work properly