AWS Data Engineer Study Roadmap

Domain 1: Data Ingestion — Kinesis Data Streams, Firehose, MSK, batch vs streaming patterns

Domain 1: Data Transformation — Glue ETL jobs, Glue DataBrew, EMR Spark, Step Functions orchestration

Domain 1: Pipeline Design — Event-driven architectures, Lambda triggers, EventBridge rules, data formats

Domain 2: Data Lake Design — S3 storage classes, Lake Formation, partitioning, Iceberg/Hudi tables

Domain 2: Data Warehouse — Redshift architecture, distribution styles, sort keys, Spectrum, materialized views

Domain 2: Catalog & Schema — Glue Data Catalog, schema evolution, Avro/Parquet/ORC formats

Domain 3: Data Pipeline Operations — MWAA (Airflow), Step Functions, Glue workflows, monitoring

Domain 3: Data Quality — Glue Data Quality rules, Great Expectations, validation and profiling

Domain 3: Troubleshooting — Pipeline failures, data skew, partition pruning, job bookmarks

Domain 4: IAM for Data — Lake Formation permissions, column-level security, cross-account access

Domain 4: Encryption & Compliance — KMS, S3 encryption, Redshift encryption, data masking, PII detection

Full Review: Practice exams, Hands-on labs, Weak areas, Exam logistics