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• Automated validation of scraped financial data from 15+ banking websites using Python (Pandas), identifying 12k+ monthly null values/mismatches and reducing data cleaning time by 25% . • Engineered Power BI dashboards to monitor pipeline health, tracking completeness rates for 50+ fields and triggering alerts for anomalies, cutting data discrepancies by 30%. • Collaborated with engineers to redesign Azure SQL DB schemas for GDPR-compliant scraped data storage, achieving 99.8% field integrity across £5M+ transactions. • Documented data lineage for HTML/JSON sources, accelerating troubleshooting by 40%.

•Validated scraped HR/finance data from SharePoint/legacy systems, resolving 200+ weekly unformatted fields via SQL ETL pipelines, improving cross-departmental report accuracy by 35%. • Spearheaded integration of alternative APIs to fill gaps in property valuation datasets, reducing null entries by 70% and enabling reliable portfolio analysis for £10M+ AUM. • Developed automated QA checks in Power BI (DAX) to flag incomplete records, decreasing manual validation time by 20 hours/month.

• Audited scraped clinical trial data (HTML/PDF) from global sources, implementing Python scripts to standardize 50+ inconsistent fields, reducing reconciliation time by 35%. • Created Tableau dashboards tracking customer engagement trends, identifying 3 high-impact behavioral patterns that informed product changes. • Trained 120+ users in self-service data validation, decreasing ad-hoc requests for missing data by 45%.