Husam Abdelqader

Product & Senior Data Platform Engineer building durable, scalable systems.

I design and build platforms and products that turn complex requirements into durable, scalable systems. My work spans data platform infrastructure, workflow orchestration, and distributed-systems architecture. I care about clean design, sound data models, and building things that stay reliable as they grow.

Experience

Education

MSc International Business - Strategy and Innovation
Maastricht University, School of Business and Economics
2026 - Present (Expected July 2027)

Skills & Tech Stack

Python FastAPI Streamlit Pandas Polars SQLAlchemy Pydantic Data Pipelines ETL Data Warehousing Stream Processing Apache Kafka Apache Airflow Apache Flink Apache NiFi Temporal Workflow Orchestration Event-Driven Architecture Distributed Systems System Architecture Data Modelling REST APIs PostgreSQL SQL Server Redis Azure Cosmos DB Gremlin Apache Druid CloudNativePG Azure Azure Functions Azure Blob Storage Azure Queues Terraform Docker Kubernetes CI/CD Git Machine Learning Power BI

Projects

Workflows Architecture

Led the architecture and data-modelling design for the Workflows Engine, a durable workflow-orchestration platform built on Temporal and Kubernetes. Designed the end-to-end system architecture, a normalized, content-addressed process-definition version store with git-like cross-environment promotion, and an order-independent event correlation and monitoring engine. Delivered as interactive architecture and ER design documents plus written specifications.

Temporal Zigflow Workflow Orchestration Durable Execution Kubernetes Kubernetes Custom Resources Azure Blob Storage SQL Server Apache Kafka REST APIs Event-Driven Architecture Data Modelling Content-Addressed Versioning Cross-Environment Promotion Distributed Systems System Architecture
Confidential

Business Process Monitoring Tool

Designed, built, and tested an end-to-end business process monitoring tool from scratch. Responsibilities included client requirements gathering, architecture design, and full-stack development.

Python Streamlit FastAPI APScheduler Redis PostgreSQL Apache Kafka Apache NiFi Docker Kubernetes
Confidential

Day-Ahead Energy Spot Market Tool

Built a custom tool for clients to prepare and process bids on the day-ahead energy spot market. Enables data-driven decision-making for energy trading operations. Features an optimization algorithm, integration with external systems, and a complete audit trail of all operations.

Python Streamlit FastAPI Redis PostgreSQL Docker Kubernetes
Confidential

Conformal Decision Rules

Researched and developed a novel machine learning algorithm capable of reliable and explainable predictions. Applied to identify at-risk patients in mental healthcare, improving patient care outcomes. Published at ECML 2022 and COPA 2022.

Python Machine Learning Scikit-learn Conformal Prediction Classification Research
View publications

Graph-Based Data Warehouse

A cloud-native Data Warehouse built on Azure Durable Functions with a graph-based architecture for enterprise data integration. Consolidates data from multiple enterprise systems into a centralized SQL Server warehouse. Features a custom ETL pipeline framework, knowledge graph data model organized using Domain-Driven Design across 10+ business domains, and serverless orchestration with fan-out/fan-in pattern for parallel execution.

Python Azure Durable Functions SQL Server SQLAlchemy Docker ETL
Confidential

Publications

Awards

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