scardoso-lu

Facilitates the ingestion of local files into Microsoft Fabric Lakehouse, ensuring data quality and lineage management.

Enables users to interpret Microsoft Fabric Semantic Models for effective DAX query writing and report building.

Facilitates the creation of Gold layer analytical objects and dimensional models for effective data analysis and reporting.

Transforms Bronze data into Silver by cleaning, deduplicating, and enforcing schema, utilizing SQL and Python for complex logic.

Validates data pipeline outputs using Great Expectations, ensuring data quality with structured PASS/FAIL reports.

Manages and maintains a Fabric data platform, orchestrating pipelines and executing operational routines for efficient data handling.

Facilitates the creation, deployment, and testing of Fabric Data Factory pipelines, ensuring efficient data processing workflows.

Generates synthetic CSV files for testing and demo purposes using the data_mock_generate tool, ensuring PII-free data for development.

Enables ultra-compressed communication for technical accuracy, reducing token usage by ~75% while maintaining clarity.

Facilitates iterative development of Fabric notebooks using a local closed-loop cycle for efficient authoring, deployment, and error management.

Facilitates in-depth discussions to refine plans or designs, ensuring clarity and shared understanding through targeted questioning.

RTK optimizes shell command token usage by 60-90%, enhancing efficiency for Git and Python workflows.