m
m_muzee

A.Abdulmuiz

@m_muzee

Data Engineer

Nigeria
Englisch, Arabisch, Yoruba
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
I help businesses automate data workflows and turn raw data into decision-ready insights. I build automated pipelines to extract, clean, and transform data from APIs, Excel, and databases, and create interactive dashboards for clear reporting. My focus is delivering scalable solutions that improve accuracy, save time, and drive better business outcomes. Tools & Technologies: Python, SQL (PostgreSQL), Power BI, Excel, APIs, ETL workflows ... Mehr lesen

Kompetenzen

m
m_muzee
A.Abdulmuiz
offline • 

Meine Dienstleistungen

Daten-ETLs
I will build automated data pipelines using python, sql, and apis
Ab15 $ / ProjektWeitere Details

Portfolio

Arbeitserfahrung

Tolaram

Business Analyst

Tolaram • Vollzeit

Dec 2024 - Apr 2026 • 1 yr 4 mos

Built automated KPI dashboards tracking performance across 12 product lines, reducing manual reporting effort by 40%. Designed ETL pipelines on GCP to ingest and transform operational data from Google Sheets into structured reporting tables. Improved data accuracy and reporting turnaround time by implementing automated validation and cleaning workflows. Conducted variance and trend analysis that helped identify underperforming regions, contributing to a 12% YoY performance improvement. Developed territory performance dashboards integrating live field data to monitor distributor KPIs, compliance metrics, and sales execution adherence across multiple regions. Built and maintained structured data pipelines to support outlet remapping and territory restructuring initiatives, enabling data-driven route optimization and improved coverage planning. Architected and deployed API-driven ETL pipelines using Python and SQLAlchemy to ingest, normalize, and load retail data into a cloud-hosted PostgreSQL database, enabling reliable downstream analytics. Implemented automated data validation and transformation rules at ingestion layer, reducing invalid records and improving overall pipeline reliability. Managed end-to-end data workflow versioning using Git and GitHub, ensuring reproducible pipeline builds and clear change history across all project iterations.