Developing Code for Data Processing using Python and SQL22%Structure Python projects for automation bundles and write the UDFs they call, build production ETL with Lakeflow pipelines, Autoloader, and Structured Streaming, handle change-data-capture and control-flow logic within them, and cover the result with unit and integration tests.
≈ 26 h Data Ingestion and Acquisition7%Ingest a mix of file formats - from Parquet and JSON to Avro - out of sources like pub/sub buses and cloud object stores, and build a single append-only Delta pipeline that handles batch loads alongside live streaming.
≈ 8 h Data Transformation, Cleansing, and Quality10%Write performant Spark SQL and PySpark transformations using windowing, joins, and aggregation, and set up a quarantine step that catches bad records before they contaminate a pipeline.
≈ 12 h Data Sharing and Federation5%Share data securely between Databricks deployments and external platforms using Delta Sharing, and configure Lakehouse Federation and live data sharing with proper governance across source systems.
≈ 6 h Monitoring and Alerting10%Watch pipeline health and resource usage through system tables, the Query Profiler, and Spark UI event logs, then set SQL-based alerts and job notifications to flag data-quality or performance problems automatically.
≈ 12 h Cost and Performance Optimization13%See how letting Unity Catalog manage your tables cuts operational overhead, apply Delta techniques like deletion vectors alongside Liquid Clustering to speed things up, and lean on the query profile when hunting down inefficient joins and shuffling.
≈ 16 h Ensuring Data Security and Compliance10%Apply data security mechanisms such as ACLs, row filters, column masks, and anonymization techniques to protect confidential data, and implement compliant pipelines that mask PII and purge data according to retention policies.
≈ 12 h Data Governance7%Attach descriptions and metadata to enterprise datasets so they're actually discoverable, and understand how permissions cascade through Unity Catalog's inheritance model.
≈ 8 h Debugging and Deploying10%Track down pipeline failures using the Spark UI along with cluster logs and system-table diagnostics, then ship the fix through automation bundles wired into a Git-based CI/CD flow.
≈ 12 h Data Modeling6%Design large-scale data models on Delta Lake, replace manual partitioning and Z-ordering decisions with Liquid Clustering, and structure dimensional models built for fast, accurate analytical queries.
≈ 7 h 
Alex