AWS Data Engineering

AWS IAM: Roles, Policies, Security Best Practices

Amazon EC2: Launching and managing compute instances

Amazon S3: Buckets, Lifecycle Policies, Object Storage Classes

AWS Lambda: Basics, Triggers, Event-driven architecture

Batch Ingestion Using AWS Glue, S3, Lambda

Streaming Ingestion: Amazon Kinesis Data Streams, Amazon Kinesis Firehose, AWS MSK (Managed Kafka)

Storage: Amazon S3 (Lake), Amazon RDS (Relational DBs), Amazon DynamoDB (NoSQL), Amazon Redshift (Data Warehouse)

AWS Glue: Crawlers, Jobs, Development Endpoints Glue Studio for visual workflows

AWS Glue PySpark Jobs: Reading/Writing from S3, Redshift, JDBC

AWS EMR: Hadoop, Spark, Hive on EMR

Lambda for lightweight ETL

AWS Step Functions : Chaining multiple AWS services

Amazon Managed Workflows for Apache Airflow (MWAA) DAGs, Schedulers, Operators, Sensors

AWS Glue Workflows Dependency management of Glue Jobs

Amazon Athena Serverless SQL over S3

Amazon Redshift Data Warehousing, Spectrum for S3 queries

Amazon QuickSight Dashboards and Business Intelligence

AWS CloudWatch : Logs, Alarms, Metrics

AWS CloudTrail: API call monitoring

AWS CodePipeline + CodeBuild CI/CD for Data Pipelines

Best Practices : Data Encryption (KMS), VPC, Subnets, Security Groups, Cost Optimization Techniques