Bio
Software Engineer turned Data Platform Engineer, specializing in AWS and Data Engineering. He contributes to building data platforms and empowers teams to grow their technical skills through hands-on collaboration.
Now, a bit more about him beyond the technical stuff: his friend and colleagues call him MohMine. Always learning, always evolving is his motto.
With love from Paris, but his heart is in Malaysia & Saudi Arabia / UAE. If he doesn't respond, he's probably training at the wrestling gym, studying, traveling, or capturing moments through his lens. He speaks French, English, Arabic/Tunisian, and would be delighted to get to know you!
Professional Availability
🇫🇷 Freelance in Paris: Open to freelance opportunities in the Paris region, with a preference for collaborations with major companies on long-term projects. He remains available for short-term interventions or specific needs as well.
🇸🇦🇦🇪 Permanent Opportunities - Gulf Region: Seeking permanent contract opportunities in Saudi Arabia or in the United Arab Emirates. His priority goes to large corporations offering stimulating challenges.
Experiences
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Air liquide
Data Platform Engineer - AWS & Alibaba Cloud
Jan 2025 — Dec 2099
Context:
Contributing to Air Liquide's digital transformation through the Unified Data Platform (UDP) serving 75+ countries.
Key responsibilities and achievements:
Lakehouse Implementation - Alibaba Cloud (Starting Q1 2026)
Contributing to lakehouse capability replication on Alibaba Cloud for APAC/China operations through architecture design, PoC, cross-functional collaboration, and APAC/China compliance frameworks.
Data Platform & Infrastructure - AWS (Jan 2025 - Present)
- Migrated from AWS Lake Formation to stable authorization system ensuring business continuity
- Maintained Infrastructure as Code (CloudFormation, CDK) for lakehouse environment (Glue, Athena, Lake Formation, DataZone)
- Implemented secure inter-account AWS access (Data Platform ↔ ML platform) via external trust and S3 unload
- Developed backend solutions (Python, FastAPI, boto3) for data ingestion and governance
- Created internal APIs for data container provisioning and DataZone access management
- Designed secure dataset preview solution bypassing Lake Formation limitations while preserving healthcare/HR data confidentiality
- Implemented CI/CD pipelines (GitLab CI, Docker, PyDoit, Poetry)
- Automated dbt testing with GitLab Runners integrated into pre-deployment validation
- Deployed API Gateway with Cognito authentication, VPC integration, and granular IAM permissions
Technical skills:
AWS, Alibaba Cloud, IaC, Python, Software Engineering, Gitlab, Data Engineering, API Design, Data Platform, Lakehouse
Business Impact:
Improved platform reliability and scalability, enhanced data accessibility for business users, enabled secure cross-platform data exchanges
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Doctrine
DataOps Engineer
Sep 2023 — Jan 2025
Context:
Worked at France's leading legal intelligence platform serving over 1 million monthly visitors and 14,000 legal professionals. Doctrine centralizes and organizes legal information to help lawyers and legal experts better advise their clients while making law more accessible and transparent.
Key responsibilities and achievements:
- Managed SalesOps infrastructure: administered and optimized back-office systems supporting client operations and internal teams
- Actively contributed to migrating critical systems (back office, APIs, Airflow, databases, AWS) to more resilient and scalable architectures
- Designed and implemented batch and real-time pipelines for processing legal and commercial data
- Deployed Infrastructure as Code solutions with comprehensive monitoring
- Developed JavaScript/Python applications and established CI/CD pipelines
- Created technical documentation and modernized legacy code
- Actively participated in technical workshops and architecture sessions related to internationalization projects
Technical skills:
Python, JavaScript, Node.js, SQL, PostgreSQL, Docker, Git, Linux, AWS (S3, EC2, RDS, Lambda, CloudWatch), Apache Airflow, Terraform, CI/CD, Metabase, RabbitMQ, REST APIs/Postman, Chargebee, Slack, CRM, Data enrichment, Software engineering, Cloud computing, DevOps
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Stellantis
Data Engineer
Jan 2023 — Aug 2023
Context:
Contributed to a financial data management project for PSA Banque Stellantis, within Quantmetry, a consulting firm specializing in data and artificial intelligence.
Key responsibilities and achievements:
- Data pipeline design and maintenance: designed, developed, and maintained data ingestion, transformation, and exposure pipelines handling up to 1 TB of financial data
- Spark optimization: improved Spark processing performance through DAG analysis and Spark UI monitoring, reducing processing time by 30%
- Mentoring & team growth: supported junior engineers and interns on data lake environments, reviewed reports, and fostered a positive team dynamic
- Automated deployment: implemented automated pipeline deployments via TeamCity, enhancing deployment efficiency and reliability
- Operational maintenance: managed the operational maintenance of PSA Banque’s data lake (monitoring, incident handling and resolution, client communication)
Technical skills:
Java · Apache Spark · Python · SQL · Hive · Bash · HDFS · TeamCity · Git · Maven · Artifactory · Apache Kafka · Amazon S3 · Kibana · Agile methodologies · JIRA · Trello · Confluence
Team:
5 Data Engineers · 1 Tech Lead · 1 Project Manager
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Decathlon
Data Engineer
Nov 2021 — Jan 2023
Context:
Contributed to a margin control automation project for Decathlon, the world’s leading sports retailer. The objective was to prevent financial penalties by systematically comparing accounting data with cash register receipts.
Key responsibilities and achievements:
- Developed a large-scale ELT pipeline processing several million records each month
- Automated financial data comparison and made results accessible to analysts
- Pioneered the implementation of dbt on Databricks with Delta Lake format — the first squad to deploy this solution at group level
- Created training materials on dbt/Databricks and supported other teams
- Set up CI/CD workflows using GitHub Actions, and DevOps templates for PySpark and Airflow
- Optimized data pipelines through Z-ordering, Spark shuffle reduction, Databricks autoscaling, and seamless integration of Delta, dbt, and Qlik
- Developed workarounds for technical constraints, such as the absence of a data rejection mechanism during ingestion
- Achieved concrete results: reduced errors, faster decision-making, and significantly fewer penalties
Technical skills:
Python · SQL · PySpark · Databricks · Amazon S3 · Amazon Athena · AWS Glue · Apache Airflow · Git · Delta Lake · dbt · Qlik · Cloud Computing
Team:
2 Big Data Engineers · 2 Business Analysts · 1 Project Manager
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Quantmetry
Data Engineer, Trainer & Meetup Organizer
Sep 2021 — Sep 2023
Data Engineer – Stellantis / PSA Avtec Powertrain Pvt. Ltd.
January 2023 – August 2023
Data Engineer – Decathlon France
November 2021 – January 2023
Designed and delivered internal and client training sessions
Topics: Advanced Python, Clean Code, Apache Airflow, Apache Spark, dbt
Organized internal technical meetups
Speakers from Back Market, Nickel, OCTO Technology, Decathlon, etc.
Co-organizer of the Paris Airflow Meetup
Data engineering / Apache Airflow community
Co-organizer of the FranceAI Meetup Group
In collaboration with TotalEnergies and Hugging Face
My coworkers' feedbacks
