Mohamed Abdulaziz Eisa

Data Engineer with 2+ years of experience designing and deploying end-to-end ETL/ELT data pipelines, building scalable data lakes and data warehouses, and developing analytics dashboards for operational intelligence. Hands-on expertise with Databricks, Snowflake, AWS (S3, EC2, Lambda), Docker, and Python. Proven ability to process daily records with high data quality and low latency.

Adept at collaborating with cross-functional teams and translating raw data into actionable business insights using Tableau, Power BI, and Grafana.

Data Engineer - ATTC-EU Automobile Technology GmbH - Deggingen, Baden-Württemberg, Germany

(2026-03)

• Design and implement ETL/ELT pipelines on Databricks to ingest and transform smart-vehicle data streams (sensor logs, driver behavior, battery performance metrics).
• Develop data tooling for storing, cleaning, and labeling large-scale datasets used to train self-driving AI models, ensuring high data quality and traceability.
• Design database schemas and maintain data lakes using Snowflake, optimizing storage costs and query performance for analytical workloads.
• Build interactive BI dashboards (Tableau, Power BI, Grafana) in collaboration with cross-functional teams to visualize real-time vehicle performance KPIs and fleet analytics.

Data Science Engineer - 15 IT Resources LLC - Hillsboro, Oregon, USA (Remote)

(2024-06 - 2025-03)

• Conducted end-to-end data pipeline development and feature engineering to surface risk and compliance patterns across large transactional datasets.
• Built and deployed 3+ predictive analytics models (Python, Scikit-Learn, TensorFlow) for risk assessment, achieving measurable improvements in predictive accuracy.
• Implemented CI/CD-enabled MLflow and Docker pipelines automating model training and deployment, significantly reducing deployment cycle time.
• Established model monitoring dashboards and quarterly retraining workflows using A/B testing to sustain production performance over time.

AWS Machine Learning Engineer – Internship - Digital Egypt Pioneers Initiative (DEPI) - Egypt

(2024-04 - 2024-10)

• Built and deployed scalable ML models on AWS SageMaker with RESTful APIs delivering sub-100ms real-time predictions.
• Implemented MLflow + Hugging Face MLOps pipelines for automated experiment tracking, CI/CD deployment, and model versioning.
• Managed distributed training on AWS EC2 clusters over a 12-week program, reducing training time via automated scaling and spot-instance optimization.

Marketing Data Analyst - Arkan Group - Egypt

(2023-05 - 2023-09)

• Analyzed large-scale marketing survey datasets using MySQL and statistical modeling in R, generating predictive insights to improve marketing analytics accuracy.
• Transformed raw marketing data into automated Excel PivotTable dashboards, enabling stakeholder tracking of performance trends.
• Converted marketing KPIs into data-driven visual narratives using Tableau, increasing decision-making efficiency for senior leadership.

Faculty of Information and communication Technology – Politechnika Wrocławska

• Master Computer Engineering

Faculty of Computer and Artificial intelligence - Benha University

• •Graduation Project: Paternity DNA Sequence Classification Using Machine Learning Algorithms and Dynamic programming (A+).