Freelancer profile translated to English.

Description

Data engineer specialized in Google Cloud Platform (GCP), I have in-depth experience in developing, implementing, and maintaining efficient and scalable data infrastructures and pipelines. My expertise on GCP allows me to design data systems capable of handling large volumes of data, thus meeting the varied needs of different stakeholders.

Why choose my GCP & Python Data Engineer services?

🔍 Python and GCP Expertise: With over 10 years of experience, I specialize in data engineering, primarily on Google Cloud Platform, offering comprehensive solutions for managing and optimizing your data.

🚀 Transforming Your Data Projects: I guide your teams in bringing data products to production, industrializing your data pipelines, and deploying microservices.

My Key Contributions:

👨‍💻 Lead Data Engineer Python GCP: Data quality management, pipeline industrialization, AI service deployment, and upskilling your teams.

⚙️ Automation and Reliability: Implementing Data Ops with Git, GitHub Actions, Cloud Build, CI/CD, and developing Site Reliability Engineering on GCP.

🌐 Designing Cloud Data Platforms: Experience in building data platforms from scratch, using BigQuery, Terraform for a solid data infrastructure.

My Technical Expertise and Practical Experience:

🌟 Successful Projects with Market Leaders: Implementing data storage architectures (L'Oréal, Veolia).

💼 Diverse Skills: Developing data pipelines (ETL/ELT), Web Scraping, creating dashboards, Python, SQL, Docker, CI/CD, Git.

💡 Complete GCP Experience: Migrating databases to BigQuery, creating data loading jobs, implementing data quality testing processes.

Languages

French
Native or bilingual
English
Fluent
Arabic
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km)

L'Oréal SA - L'Oréal France
Data Engineer
FASHION AND COSMETICS
September 2020 - Today (5 years and 10 months)
Paris, France
Development and deployment of architectures on GCP:

- Database Migration and Optimization: Leading complex migrations to BigQuery

- Data Pipeline Development and Maintenance: Creating data extraction and ingestion modules (approx. 50 databases x 20 tables), and implementing SQL procedures for KPI calculation.

- Analysis and Reporting: Designing tables and views for analysts, facilitating data access and result interpretation.

- Quality Assurance and Compliance: Establishing unit testing processes in CI/CD and implementing data quality control processes.

- Cloud Infrastructure and Tools: Managing machine provisioning and deploying tools on the GCP platform, including Cloud Run, Storage, Pub/Sub, Firestore, Cloud Workflows

Mastered Technologies:

Python, Terraform, Google Cloud Platform (BigQuery, Cloud SQL, Cloud Workflows, Composer, and more), CI/CD, Git.
python Terraform Google Cloud Platform Big Query GCP PubSub BigQuery Cloud Run Cloud Workflows Composer
Veolia
Data Engineer
ENERGY AND UTILITIES
December 2017 - June 2020 (2 years and 6 months)
Paris, France
Building and implementing a data lake:

- Diverse Data Collection and Integration: Acquiring data from various sources such as CSV, JSON, APIs

- Data Ingestion: Implementing batch and streaming data ingestion via Google Dataflow, processing over 40 TB of data.

- Data Storage Tools Development: Creating tools for storing data in BigQuery, Cloud SQL, Datastore, and Firebase.

- View Management System: Implementing a view management system to expose data to sales teams.

- Data Catalogue Web Application Development: Designing a web application for the data lake using Flask and Angular.

- Expertise in Modern Distributed Architectures: In-depth knowledge of distributed architectures and technologies for computation, data analysis, and storage on GCP.

Mastered Technologies:

Python, Google Cloud Platform (including Dataflow, Storage, Pubsub, Datastore, BigQuery, Cloud SQL, Firebase, App Engine, Cloud Functions, Cloud Run), CI/CD, unit tests.
Google cloud Python Git Dataflow Firestore Firebase Google App Engine Cloud Functions flask
Searchub
Backend Engineer
E-COMMERCE
December 2012 - September 2017 (4 years and 9 months)
San Francisco, United States
Searchub is an e-commerce price comparator with over 200M products.

- Infrastructure on AWS: Setting up and managing a Hadoop cluster on AWS.

- Extraction, processing, and integration of data into a global database, ensuring smooth and efficient product information management.

- Automatic Product Categorization and Matching Solution: Developing an innovative solution for automatic product categorization and matching, enhancing the accuracy and relevance of results for users.

- Handling and Categorization of Multiple Data: Merging and organizing data from numerous sources into a unified database, optimizing information accessibility and utilization.

- Experience in NLP and Machine Learning: Applying natural language processing (NLP) and machine learning techniques to refine platform functionalities and improve user experience.
Python Amazon Web Services AWS SEO Google AdWords HBase Solr Hive