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