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Mohamed Taha
Abo Heiba

Building data systems that are reliable by design,
maintainable in practice, and useful to the business.

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0 End-to-end projects
240ms Production API latency
0 Industry certifications
Mohamed Taha Abo Heiba
#1 / 30+ Best-performing trainee
NTI Huawei Big Data cohort
~240ms Avg Latency End-to-end production latency
RAG pipeline · Hugging Face
2 Certs AWS CLF-C02 & Huawei HCIA Big Data
both first attempt
// about

Approach & Background

I approach data infrastructure as a systems problem, not a scripting task. A pipeline that runs once is not the same as one that runs reliably every day, and the gap between those two things is where most engineering decisions live: schema contracts, failure handling, execution logging, partition strategy, layer separation.

My work spans the full data stack, from raw ingestion to governed, analytics-ready outputs. SQL Server warehouses with stored-procedure transformation layers. Databricks lakehouses built on the Medallion architecture with Unity Catalog for lineage. FastAPI retrieval systems backed by vector stores. Each system is designed to be debuggable, reproducible, and maintainable, not just functional.

Certified in Huawei HCIA-Big Data (best trainee across 30+ participants, first attempt) and AWS Cloud Practitioner. Computer Science degree, GPA 3.4/4.0.

Increasingly focused on DE for AI workflows: building and benchmarking vector store pipelines, embedding systems, and retrieval APIs that run in production. Same reliability principles apply, schema contracts at ingestion, measurable latency, and clean separation between indexing and serving. Retrieval quality is measured with an offline evaluation harness, not assumed.

Get In Touch
taha@pipeline ~ bash
taha@pipeline ~ $
These principles shape every system I build
// engineering workflow

How I Engineer Data Systems

A business question becomes a reliable data product through deliberate stages. Select any stage to see the reasoning, goal, principles, and projects that prove it in practice.

Here is how these principles become production systems
// portfolio

Projects

The systems are backed by hands-on engineering experience
// work history

Experience & Training

AWS Cloud Data Engineer Trainee Oct 2025 to Dec 2025
NTI, National Telecommunications Institute  ·  Digital Egypt Youth Program
  • Architected a multi-tier cloud data platform on AWS from S3 static hosting to a production-grade EC2/RDS/VPC architecture, applying Well-Architected Framework principles across compute, storage, and networking layers.
  • Configured RDS Multi-AZ with automated failover and S3 data lifecycle policies (Standard to Infrequent Access to Glacier) for cost-optimised cloud storage management.
Big Data Engineer Trainee Jul 2025 to Sep 2025
NTI, National Telecommunications Institute  ·  Huawei Big Data Program
Best-Performing Trainee, Exam Voucher Awarded
  • Awarded best-performing trainee across a cohort of 30+ and earned a Huawei exam voucher, passing the HCIA-Big Data certification on the first attempt.
  • Built GB-scale Spark batch pipelines on Hadoop (HDFS/YARN/Hive) and Kafka + Flink streaming pipelines for real-time log ingestion across 15+ hands-on labs.
Data Engineer Trainee Apr 2024 to Oct 2024
DEPI, Digital Egypt Pioneers Initiative
  • Built 4 SSIS ETL packages ingesting 7 CSV data sources into SQL Server via 17 stored procedures, automating data ingestion and transformation workflows end-to-end.
  • Delivered a validated dataset of 70K records powering a customer churn model, achieving 97.4% accuracy, enabling data-driven retention strategies.
// credentials

Certifications

Huawei Technologies
HCIA, Big Data Associate
Issued Mar 2026  ·  Valid until Mar 2029
Cert No. 010101801855810426731409
Best-Performing Trainee · Passed on First Attempt
Amazon Web Services
AWS Certified Cloud Practitioner (CLF-C02)
Issued May 2026  ·  Valid until May 2029
AWS Certified · Cloud Practitioner
// tech stack

Tools & Technologies

Pipeline Engineering
PySpark Delta Lake Databricks SSIS Medallion Architecture Kafka ETL/ELT patterns Batch Processing Airflow Flink
Storage & Warehousing
SQL Server Star Schema Unity Catalog Dimensional Modeling HDFS HBase Snowflake Schema Galaxy Schema
Cloud (AWS)
S3 EC2 RDS IAM VPC Lambda CloudWatch Glue Redshift Athena
Languages & APIs
Python T-SQL FastAPI Pandas Bash NumPy
AI Data Engineering
RAG Pipelines LangChain ChromaDB Qdrant Embeddings Hybrid Retrieval Retrieval Evaluation Generation Evaluation LLM API
Analytics & Tooling
Power BI DAX Power Query Git Docker Matplotlib Linux
// background

Education

Oct 2022 to Jun 2026
Bachelor of Science, Computer Science
Fayoum University  ·  Faculty of Computers and Artificial Intelligence
GPA 3.4 / 4.0. Core coursework: Big Data Engineering, Cloud Computing, Database Management Systems, Advanced SQL, Data Structures & Algorithms, Machine Learning, Operating Systems (Linux, Docker), Python Programming, Data Visualization (Power BI).

Graduation Project: EduMate, a unified academic management platform with an RAG chatbot built on LangChain, ChromaDB, and Qdrant.
// let's talk

Get In Touch

Actively looking for Data Engineering, Big Data, and Cloud Data Engineering roles. If you're building data infrastructure, pipelines, or lakehouses, reach out. I respond within 24 hours.

LinkedIn linkedin.com/in/mohamed-taha-abo-heiba
GitHub github.com/MoTahaAboHeiba
WhatsApp +20 114 971 1922
Email Mohamed-aboheiba@outlook.com
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