Open to opportunities

Emmanuel Alabi

@emmanuelalabi1

Data Analyst focused on clean, actionable insights—building interactive dashboards with SQL, Power BI, Python, and Tableau.

Nigeria

Message

What I'm looking for

I’m looking for a role where I can deliver data-driven decisions—cleaning and validating datasets, writing strong SQL, and building clear dashboards with Power BI/Tableau, while maintaining database integrity and collaborating to improve business outcomes.

I’m a Data Analyst who turns messy, real-world data into clear, reliable insights. At QwamPay (remote), I collected and standardized company information across Nigeria for the TelAfrik platform, then cleaned and validated datasets using Excel, SQL, and Python (pandas) before loading to production.

I’m also passionate about building data capability—through teaching. As a Data Analytics Tutor at Tech Talent Academy, I helped learners create interactive visualizations in Power BI and Tableau, use DAX for calculated metrics and KPIs, and apply data cleaning workflows with Power Query and Python. I’ve complemented this with hands-on projects like a Cancer Patient Survival & Severity Analysis dashboard (Power BI, DAX measures) and a Car Sales Insights dashboard (Excel, Power Query), plus coursework-level exposure to predictive modeling techniques for better decision-making.

Experience

Work history, roles, and key accomplishments

Current

Data Analyst

Current

QwamPay

Jan 2026 - Present (4 months)

Collected, cleaned, and standardized company data across Nigeria for use on the TelAfrik platform, ensuring up-to-date coverage and reliable information delivery. Wrote and optimized SQL queries in Supabase, performed database audits to resolve inconsistencies, and transformed data for seamless site integration.

SQL Supabase Excel Data Validation Data Cleaning Data Auditing Data Integration Relational Databases Data Modeling

Data Analytics Tutor

Tech Talent Academy

Feb 2025 - Oct 2025 (8 months)

Taught students to build clear, interactive dashboards and visualizations in Power BI and Tableau to identify strengths and weaknesses. Instructed learners on sales data analysis with DAX, dataset cleaning and preprocessing with Power Query and Python (pandas), and preparation for machine learning modeling.