Manuel M.

I bridge the gap between heavy cloud infrastructure, corporate data architecture, and executive analytics. Instead of just creating visual dashboards over broken spreadsheets, I engineer the underlying database pipelines in Google BigQuery and Python to ensure your data infrastructure scales without errors. My background combines experience as a Commercial Strategy Director, a Physics/Chemistry Educator, and structural logic. This allows me to map complex business bottlenecks into strict relational database schemas, document systems clearly, and align technical teams with C-level requirements. How I work across the data lifecycle: Cloud Infrastructure & BigQuery: I audit raw inventory datasets and design relational schemas, managing complex data types and setting up strict validation layers optimized for high-volume API endpoints and marketplace search algorithms. Python Data Engineering & Pipelines: I build automated data parsing scripts and cleansing pipelines using Pandas and RegEx to handle unstructured text logs, missing variables, and outlier mitigation over datasets with tens of thousands of rows. Executive Power BI Solutions: I transform that backend infrastructure into clean, interactive dashboards (DAX/Power Query) that management teams actually use to track P&L, sales velocity, and operational KPIs across multi-location organizations—with past frameworks deployed for over 900 locations. Tech Stack: Google BigQuery, Power BI, Python (Pandas, Scikit-Learn), SQL, Looker Studio, and direct integrations with high-volume e-commerce tools (Ordoro, eBay APIs) and ERP/CRM systems. As an Upwork Top Rated consultant with a 100% Job Success Score, I operate independently under loose specifications. Let’s do a brief call to discuss your current data architecture and operational bottlenecks.