Hybrid
Full Time
1. Airflow Workflow orchestration tool (DAGs = tasks + dependencies) Components: Scheduler, Executor, Workers, Webserver, Metadata DB Features: retries, alerts, integrations with cloud services 2. Python Core scripting for ETL, automation, APIs Key: loops, functions, error handling, OOP, libraries (pandas, sqlalchemy) 3. SQL Querying & transforming data Skills: joins, aggregations, window functions, subqueries, performance tuning 4. Data Warehousing Centralized storage for analytics Concepts: fact vs dimension tables, star/snowflake schema, partitioning, clustering 5. GCP Data Engineering BigQuery (analytics), GCS (storage), Dataflow (processing), Pub/Sub (streaming), Composer (Airflow) IAM & service accounts for security 6. ETL Extract (sources), Transform (clean/aggregate), Load (warehouse) Best practices: incremental loads, error handling, schema evolution, monitoring
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