Victor Kipruto Rop

// AVAILABLE FOR INTERNSHIPS · 2026

Victor Kipruto Rop

Data Engineer · Pipeline Architect · Data Architect

Building production-grade data systems that scale. From Kafka streams to Airflow orchestration. Experienced in designing reliable ETL, low-latency streaming, and warehouse modelling. Based in Nairobi, Kenya.

4+ Production Projects
20+ Technical Skills
3 Certifications
2028 Expected Graduation

About Me

Victor Kipruto Rop Data Engineer in training

I'm a BSc Data Science student at The Cooperative University of Kenya, building a career at the intersection of scalable systems and trustworthy data.

My work is driven by a belief that clean, well-engineered data infrastructure is what separates organisations that can act on their data from those that only think they can.

Most of that work has centered on Kenya's mobile money rails specifically: M-Pesa transaction pipelines, Safaricom's Daraja API, and the reconciliation problems that come with a payment network processing at national scale. It's a narrow, underserved niche globally, and one where the infrastructure challenges are genuinely different from a typical Stripe or PayPal integration.

University The Cooperative University of Kenya
Degree BSc Data Science · Expected August 2028
Location Nairobi, Kenya
Status Open to Data Engineering internships
GitHub github.com/Victor-Kipruto-Rop

Learning & Project Experience

PesaGuard: FinTech Reconciliation Platform

Independent Product · Live Pilot

2026 – Ongoing

What I built

A real-time M-Pesa reconciliation and anomaly-detection platform: a Flask backend that ingests Safaricom Daraja webhook events, an idempotency-guarded reconciliation engine, a PostgreSQL data layer, and a Next.js 14 admin dashboard for monitoring transactions, match rates, and open anomalies.

What problem I solved

Kenyan SACCOs, e-commerce operators, and small fintechs had no reliable way to reconcile M-Pesa payments against their own ledgers. It was typically a manual, end-of-day spreadsheet exercise. Worse, Safaricom retries webhook deliveries, so duplicate transactions were a certainty, not an edge case, with nothing in place to catch them.

Technologies

Flask Python Next.js PostgreSQL Daraja API

Impact

Live in production with one pilot customer processing real M-Pesa transactions. Shipped webhook idempotency, the highest-priority risk in the system, verified end-to-end across the reconciliation engine, so a retried or duplicate webhook can never be double-counted. Also produced a target-state architecture spec scoping the platform to 100M transactions/day.

BSc Data Science Student

The Cooperative University of Kenya

Expected Aug 2028

Over the past year, I've specialized in data engineering and have built production-grade data systems through hands-on projects. Designed and implemented scalable ETL pipelines, real-time stream processing with Kafka, and warehouse infrastructure. These projects have equipped me with deep technical skills in Python, SQL, Airflow orchestration, and cloud architecture.

Python Apache Airflow Kafka PostgreSQL ETL/ELT

Hands-On Project Development

Building Real-World Data Infrastructure

Last 12 Months

Completed 5 major projects involving data pipeline design, cloud ETL systems, real-time transaction streaming, and warehouse optimization. Each project has significantly strengthened my understanding of production systems, best practices, and scalable architecture. I'm committed to continuous learning, eager to gain from experienced professionals, and passionate about building reliable data systems that drive organizational value.

Docker SQL Cloud Architecture System Design CI/CD

Technical Skills

Tap any skill for why I use it, where I've used it, and the project behind it

Orchestration & Pipelines

Streaming & Real-Time

Data Modeling & Warehousing

Data Quality & Reliability

Languages & Databases

DevOps & Testing

Data Processing Libraries

Visualisation & Analysis

Professional Certifications

IBM

IBM / Cognitive Class

Big Data Foundations

Comprehensive training in big data concepts, Hadoop ecosystem, and distributed computing fundamentals.

Big Data Hadoop IBM Cloud
IBM

IBM

Enterprise Design Thinking

Mastered user-centered design principles and collaboration techniques for solving complex business problems.

Design Thinking User Experience Problem Solving
VC

Verified Credential

Professional Development

Continued learning and specialization in scalable data systems and engineering best practices.

Data Engineering Systems Architecture

Impact, By the Numbers

What the work has actually produced, not just what it uses.

70,000/sec
Peak ingestion throughput on the Cloud ETL Ingestion Pipeline
38/38
Tests passing, gating every deploy to the Kenyan Market ETL Pipeline
100M/day
Transaction scale scoped in PesaGuard's target-state architecture spec
Zero
Duplicate transactions from Daraja webhook retries, by design
4min → 45s
Full batch load time cut via connection pooling and batch tuning
6
Production data systems shipped, from streaming to reconciliation

Hey there 👋

Open to internships & data collabs. Message me on WhatsApp.