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Marion Racheal Nyaboe Sure

Data Engineer | SQL | Python | ETL | Data Validation | BI Reporting

Nairobi, Kenya

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Professional Summary

I am a Data Engineer with a strong background in software development and analytics. I design automated reporting pipelines, perform structured data validation, and build dashboards that support operational and executive-level decision-making.

My professional experience includes service-oriented and public-sector contexts, where data accuracy, documentation, and system reliability are critical. Skilled in SQL, Python, relational databases, ETL workflows, and cloud technologies. I focus on building reliable, scalable, and well-documented data systems and I am seeking opportunities to continue developing as a data engineer, particularly in roles that involve cloud-based data systems and analytics-ready data infrastructure supporting evidence-based decision-making.

Resume Overview

Education

BSc. Software Development

KCA University (2018 – 2023)

Skills

Languages & Tools: SQL, Python (Pandas, Matplotlib), Excel, Power BI, Tableau, Looker Studio

Data Analytics: Exploratory Analysis, Data Cleaning, Data Validation, Dashboard Reporting

Databases: MySQL, PostgreSQL

Data Engineering: ETL Workflows, Airflow, Apache Spark

Cloud: AWS (S3)

Experience Highlights

  • Automated reporting pipeline across 17 sub-counties, reducing manual reporting time
  • Validated 20,000+ structured records to ensure data accuracy
  • Designed performance dashboards for leadership to track KPIs
  • Built telecom analytics reporting systems to support decision-making

Data Projects

Green & Clean Automation Pipeline

Developed automated reporting dashboards to replace manual WhatsApp reporting. Increased reporting efficiency and accuracy.

Stack: Google Forms, Sheets, Looker Studio

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Bursaries Allocation Dashboard

Built interactive dashboard tracking funding trends and allocation distribution to improve transparency and decision-making.

Stack: Excel, Looker Studio

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Lab Challenges

Netflix EDA (Python)

Exploratory analysis to identify genre dominance, content growth trends, and production distribution.

Tools: Pandas, Matplotlib

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Titanic Survival Model (Kaggle)

Applied feature engineering and classification modeling to analyze survival predictors and improve prediction accuracy.

Tools: Scikit-learn

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HR Analytics Dashboard

Developed interactive dashboard analyzing attrition, workforce distribution, and tenure trends to support HR decision-making.

Tool: Tableau

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Contact

Email: mnyaboe33@gmail.com

Phone: +254 769 467 742

LinkedIn GitHub