VictorSabare
Modernizing bank-grade pipelines that safeguard 0+ SLAs across Finance, Risk, and Operations
Transforming raw data into actionable insights through modern data engineering practices, cloud-native architectures, and real-time processing systems.
Proven Track Record
Delivering data solutions that drive business growth and innovation across industries
Data Processed
Across multiple industries
Projects Completed
Successful data solutions
System Uptime
Reliable infrastructure
Records Processed
Daily processing capacity
Technologies
Mastered and implemented
Client Satisfaction
Based on project feedback
These featured posts launch on Medium so you can read the full story where they were originally published.
Read on MediumFresh writing on data engineering, analytics, and architecture from my Medium publications.
Optimising Multi Cloud Data Pipelines (Without Losing Your Shit)
Two years ago I moved a “simple” pipeline from one cloud to another for a project . By week two my Slack looked like a heart monitor… Continue reading on Towards Data Engineering »
Careers in Data Engineering 2025: New Roles and Skill Paths
“Do you see yourself as a guardian of data pipelines or the bridge between code and business strategy? In 2025, you can be both.” Continue reading on Data Engineer Things »
The Data Engineer’s Toolkit: 12 Free Monitoring Dashboards You Didn’t Know Existed
How I stopped firefighting and reclaimed my weekends, without spending a dime Continue reading on Data Engineer Things »
A showcase of data engineering solutions and platforms I've architected and built.
Detecting & Classifying Fraudulent Ethereum Accounts
Developed a machine-learning framework combining supervised and unsupervised methods to detect fraudulent Ethereum accounts with >85% accuracy and <5% false positives, deployed as an interactive Streamlit app.
Real-Time Analytics Platform
Built a comprehensive real-time analytics platform processing 10M+ events per day using Kafka, Spark Streaming, and ClickHouse for sub-second query performance.
Stock Price Prediction Spark Cassandra
This is a data pipeline for predicting stock prices using Apache Spark, Apache Cassandra, and machine learning techniques. It collects and preprocesses stock data from Alpha Vantage API, engineers features, trains models, and performs data analysis and predictions.
Stock Price Data Analysis
This repository contains the code and analysis for my data analysis project on stock price analysis and forecasting for my Internal attachment at Jomo Kenyatta University of Agriculture and Technology. The project analyzes historical stock price data, visualizes trends, and develops a forecasting model using Python and data science techniques.
Dag Pipeline With Dbt
The project focuses on the development and deployment of an ELT (Extract, Load, Transform) pipeline utilizing industry-standard tools such as dbt (data build tool), Snowflake, and Airflow. The pipeline is designed to handle the transformation and loading of data from source tables to final data marts, ensuring efficient data processing.
Product Network Analysis Using R
This Shiny web application analyzes product transactions to discover frequently purchased product pairs and visualize the relationships between them. The app uses association rule mining (Apriori algorithm) to identify frequent itemsets, and it applies community detection to find clusters of related products.