Apart from stored procedures, have you worked on cloud services, EMR, and Lambda functions?

I have hands‑on experience with Amazon EMR and AWS Lambda in the context of data processing pipelines. In my last role, I designed a Spark job that ran on EMR to transform raw logs into a structured format, then triggered a Lambda function to push the results into DynamoDB. The Lambda was responsible for performing lightweight validation and enrichment before persisting the data. I also used Lambda to orchestrate the workflow, invoking the EMR step function and handling retries. For cloud services, I have worked with S3 for storage, IAM for fine‑grained access control, and CloudWatch for monitoring. While I haven’t written complex stored procedures, I have used them in a relational database to encapsulate business logic and to provide a stable API for downstream services. My experience spans from setting up the EMR cluster, tuning Spark configurations, to writing Lambda handlers in Python and deploying them via Serverless Framework. I’ve also managed the CI/CD pipeline for these services using CodePipeline and CodeBuild, ensuring that changes are automatically tested and deployed.