Data Engineer / Data Science Graduate / Data & AI
I build reliable data systems — pipelines, warehouses, and AI-powered applications that turn raw data into decisions teams can trust.
The full data engineering lifecycle I work across — ingestion, storage, transformation, orchestration, and serving — built on tools from the ATHAR bootcamp and hands-on projects.
I'm a Data Science graduate with a strong focus on Data Engineering, Data Analytics, and AI-powered applications — hands-on across Python, SQL, ETL pipelines, databases, dashboards, and full-stack machine learning workflows.
My background combines academic study with practical training: a co-op at King Fahad Medical City, the ATHAR Data Engineering Bootcamp, professional certificates from IBM and Cisco, and my graduation project, HealAI.
I care about building reliable data solutions, transforming raw data into meaningful insight, and developing intelligent systems that support smarter decision-making.
University of Hafr Al Batin · Database Systems, Big Data Analytics, Data Mining, Machine Learning, Statistics
A full-stack, AI-powered healthcare platform for wound image classification and health assessment.
React · TypeScript · FastAPI · TensorFlow / Keras · ResNet50
HealAI lets users upload wound images and receive AI-based classification results, health recommendations, a disease encyclopedia, and body analysis tools — connected end-to-end through REST APIs between the frontend, backend, and AI model server.
Organized the way data flows — refined through the Medallion architecture into progressively higher-quality, decision-ready layers.
Ingest and land data as-is — Kafka streams, REST APIs, files, and source extracts captured for traceability.
Clean, validate, and model — deduplicated, conformed datasets with integrity checks ready for analysis.
Business-ready aggregates feeding dashboards, KPIs, and machine learning — the layer decisions run on.
Python, SQL, Airflow, Kafka, Spark, Hadoop, Microsoft Fabric, Azure, Power BI, Lakehouse & Medallion architecture.
Relational databases, SQL, BI tools, ETL, Python, NoSQL, Apache Spark & Hadoop, plus a capstone project.
Database design & security, SQL, backups, automation, performance tuning, Airflow, MySQL & PostgreSQL.
Data science methodology, Python, SQL, data analysis & visualization, machine learning, applied capstone.
AI concepts, machine learning, deep learning, NLP, computer vision, neural networks, and AI ethics.
Prioritization frameworks for deciding what to build and where to focus product effort.
Open to Data Engineering, Data Analytics, and AI opportunities. Reach out — I'd be glad to talk.