I help businesses troubleshoot ETL pipelines and improve data quality before bad records reach reports, warehouses, or downstream systems.

Typical work includes:

• Investigating failed or unreliable ETL jobs • Validating required fields, formats, and business rules • Identifying duplicates, missing values, and invalid records • Reconciling source data against warehouse or report totals • Cleaning and standardizing data with SQL or Python • Adding practical logging, exception outputs, and quality checks • Documenting findings and recommended next steps

To get started, please provide a sanitized sample, source and target table definitions, expected results, error messages or sample exceptions, and any relevant schedule or transformation details.

I do not need production credentials or direct database access. Please do not send passwords, confidential data, or sensitive customer information.