Amin Al-Ait

About

Cloud Data Engineer with 4+ years of hands-on AWS experience, specialising in designing and delivering scalable, cloud-native data platforms. I thrive at the intersection of data engineering, DevOps, and backend development — turning messy, high-volume datasets into reliable, cost-efficient pipelines.

Most recently I led the data platform modernisation for a global automotive enterprise, cutting analysis costs by over 50% and time-to-result by over 75%. I work with Python, Terraform, and the broader AWS data stack every day, and I bring rigorous testing practices (full pyramid) to everything I ship.

4+ Years AWS

3+ Years Data Eng.

2 AWS Certs

3 Languages

Skills

Cloud & Infrastructure

AWS
Terraform (IaC)
AWS Lambda
AWS ECS
AWS S3
AWS API Gateway

Data Engineering

ETL Pipelines
AWS Athena
AWS Glue
Parquet / PyArrow
InfluxDB
Data Mining

Development & Testing

Python
Backend Development
ETL Testing / QA
Pyramid Testing
CI/CD (GitLab)
Monitoring & Observability

Platforms & Tooling

GitLab
cplace (No/Low/Pro-code)
Agile / Scrum
GenAI-assisted Dev

Experience

Automotive

Led the design and delivery of a cloud-native data analysis platform for a global automotive client, replacing a manual Excel-based process. The platform reduced analysis costs by >50% and time-to-result by >75%, and laid the groundwork for future AI-driven analytics.

Developed data pipelines processing large datasets with secure, reliable transformations.
Implemented a full ETL Testing Strategy covering the entire Testing Pyramid.
Managed infrastructure deployment via Terraform across AWS Lambda and ECS.
Verified end-to-end data integrity from source to persistence layer.
Leveraged GenAI for workflow optimisation and EDA on complex data formats.

PythonAWS LambdaAWS ECS AWS S3AWS AthenaAWS Glue TerraformGitLabParquet cplaceNo-codeLow-codePro-code

Sports Tech

Contributed to a mobile running coaching application, building the entire backend from scratch in a small, agile team alongside a professional runner and a frontend developer.

Developed and owned the complete backend for the running coaching app.
Implemented GPS data analysis to assess athlete pace and geolocation performance.
Designed a scalable, cost-effective serverless architecture on AWS.

AWS LambdaAWS S3AWS API GatewayGitHub

Certifications

☁

CLF-C02

AWS Certified Cloud Practitioner

Amazon Web Services

⚙

DEA-C01

AWS Data Engineer Associate

Amazon Web Services

Languages

English Native / Expert

Arabic Native / Expert

German Basic

Projects

A serverless AWS engine that surfaces hidden economic and geopolitical relationships between nations.

Ingests decades of World Bank indicator data and computes cross-correlations across all country pairs, synthesising raw signals into Patterns, Influence Cascades, and Relationship Clusters. Orchestrated by a 6-phase AWS Step Functions state machine spanning Lambda, Batch (Graviton Spot), Glue, and Athena.

PythonAWS Step FunctionsAWS Batch AWS GlueAWS AthenaParquet

Full project breakdown ↗

Latest Writing

23 Mar 2025↗ Medium

How Quran Saves The Arabic Language

ArabicLanguageHistory

06 Mar 2025↗ Medium

NATO Doctrine at Strategic Crossroads

NATOStrategyEurope

17 May 2023↗ Medium

The Weak Link in the Russia–Iran–India Railway: Surprisingly, It's Not Iran

RussiaIndiaInfrastructure

All posts ↗

Contact

Whether you're interested in what QGI patterns reveal about your region or sector, want to discuss a cloud data engineering engagement, or are looking to recruit — reach out.

Email AminAlAit@outlook.com

LinkedIn aminalait