Julius Matheka
Charles
Software Engineer · Data Engineer · AI & ML Developer
Results-driven Software & Data Engineer with hands-on experience across the full data lifecycle — from pipeline design and SQL analytics to Python backend development and BI reporting. Building reliable, scalable systems with AI/ML integration.
About Me
Turning complex data into actionable insights and building reliable, scalable systems
I'm a Software & Data Engineer with hands-on experience across the full data lifecycle — from pipeline design and SQL analytics to Python backend development and BI reporting. I specialise in turning complex data into actionable business insights and building reliable, scalable systems.
With a Computer Science foundation and professional certifications in Software Engineering and Data Science, I've built a career across data engineering, backend development, and AI/ML integration — always focused on writing clean, maintainable code and delivering impactful solutions.
I bring a strong foundation in Agile delivery, cloud-native tools, and AI/ML integration. I'm always eager to take on new challenges and collaborate on projects that push the boundaries of what's possible.
Data Engineering
PostgreSQL · ETL/ELT · Airflow · Kafka · pgvector
AI / ML Integration
LangChain · OpenAI · RAG · Semantic Search · Claude
BI & Analytics
Power BI · Tableau · Dashboards · DAX · Data Modeling
Python Backend
Django · DRF · FastAPI · Celery · pytest
Years Experience
Professional Roles
Technologies Mastered
Commitment
Skills & Expertise
A comprehensive overview of my technical skills and proficiency levels
Data & SQL
BI & Analytics
Python
AI / ML
Frontend
DevOps
Key Projects
A showcase of my recent work in AI integration, data engineering, and full-stack development
Prepzi — Smart Meal Planning App
2025 – PresentAI-powered meal planning that reduces food waste by 90%. Generates personalized weekly/monthly plans from your inventory, with smart shopping lists, 10+ cuisines, dietary preferences, and offline-first sync.
LezMarket — AI Website Conversion Optimizer
2024SaaS tool that scores homepages against persuasion principles, generates AI recommendations, and stores structured analysis history per user.
Synovae — AI Job Matching Platform
2024Semantic CV-to-job matching engine across 2,400+ live roles using LLM embeddings, with automated application tracking in Supabase.
Work Experience
My professional journey in software development, data engineering, and BI analytics
Junior Python Data Engineer
Designed and implemented end-to-end data pipelines in Python and SQL — covering raw ingestion, staging, transformation, and analytics layers across PostgreSQL databases.
Built and scheduled Apache Airflow DAGs to automate recurring ETL jobs, replacing manual processes and improving data freshness for downstream consumers.
Engineered a semantic job-matching pipeline using Python, LangChain, and pgvector — parsing CVs and vectorising content for similarity search across 2,400+ live listings.
Implemented incremental loading patterns (upsert / ON CONFLICT DO UPDATE) and run logging to support efficient, restartable pipeline execution at scale.
Delivered a RAG-powered knowledge base using PostgreSQL/pgvector and LangChain, achieving sub-3-second query latency under load in production testing.
Junior Python Developer
Wrote complex SQL queries across PostgreSQL databases to extract, clean, and analyse business datasets for weekly management reporting.
Built and maintained ETL pipelines that pulled data from multiple source systems into a central data warehouse, reducing manual data preparation time by 35%.
Created data quality checks using SQL (NULL validation, duplicate detection, row count reconciliation) to ensure pipeline integrity across all reporting tables.
Collaborated with senior analysts to design dashboard-ready summary views and aggregation tables consumed by Power BI reports.
Documented SQL query logic and pipeline steps, improving team knowledge sharing and onboarding efficiency.
Data Analyst Intern (SQL)
Wrote complex SQL queries across PostgreSQL databases to extract, clean, and analyse business datasets for weekly management reporting.
Built and maintained ETL pipelines that pulled data from multiple source systems into a central data warehouse, reducing manual data preparation time by 35%.
Created data quality checks using SQL (NULL validation, duplicate detection, row count reconciliation) to ensure pipeline integrity across all reporting tables.
Collaborated with senior analysts to design dashboard-ready summary views and aggregation tables consumed by Power BI reports.
Documented SQL query logic and pipeline steps, improving team knowledge sharing and onboarding efficiency.
Education & Certifications
My academic background and professional certifications
Education
Professional Certification — Software Engineering
Full-stack development, algorithms, Django/React, Java/Spring Boot.
Professional Certification — Data Science
Machine Learning, ETL pipelines, Python, SQL, TensorFlow, Tableau.
B.Sc. Computer Science
Strong foundation in algorithms, data structures, software engineering, and systems design.
Certifications
ETL and Data Pipelines with Shell, Airflow & Kafka
IBM
Data Warehousing and BI Analytics
IBM
Linux Commands and Shell Scripting
IBM
Get In Touch
I'm always open to discussing new projects, creative ideas, or opportunities to be part of your visions.