Arslan Ijaz

• Built end to end data pipelines for multi sensor healthcare systems, integrating BLE vibration sensors, PIR motion sensors, sleep sensors, and fall detection devices into Couchbase and downstream databases.
• Developed FastAPI services for data ingestion, extraction, and designed Airflow based post processing pipelines (running every 5 minutes) to clean, transform, and route sensor data into PostgreSQL, InfluxDB, and Couchbase.
• Integrated ML models (anomaly detection, ADL recognition, sleep disorder indicators) into production pipelines, ensuring scalable deployment and low latency inference.
• Collaborated with cross functional teams to deliver production ready data engineering solutions meeting clinical and operational requirements.

• Delivered core data engineering components for the global CCP logistics platform, processing large scale vehicle shipment data from Toyota, Hyundai, BMW, Mercedes Benz, and Caterpillar, etc.
• Built Azure based ingestion pipelines to process multilingual distributor files (Excel, CSV, email attachments) and standardize heterogeneous formats into a unified data model.
• Automated ingestion and transformation processes, reducing manual intervention and improving operational efficiency.
• Collaborated with distributed engineering and operations teams across multiple regions, ensuring smooth integration of data sources, alignment on technical requirements, and consistent delivery across global stakeholders.

• Managed and monitored ETL pipelines for Pakistan’s largest private credit bureau, processing weekly credit data submissions from 110+ financial institutions (microfinance banks and commercial banks).
• Performed ad hoc financial and operational analyses, ensured data quality, consistency, and compliance across large scale ingestion workflows.

• Analyzed BTS site data and identified a targeted optimization strategy showing that focusing on 600 high impact sites (out of 13,000) could reduce fuel consumption costs by up to 35%.
• Designed interactive Power BI dashboards (Fuel Status, TCH, LS) to monitor different parameters in near real time that significantly improving operational transparency.

Master's degree focusing on data science principles and applications.

Bachelor's degree in Electrical Engineering covering foundational engineering concepts.

Completed pre-engineering studies as preparation for engineering discipline.