Freelancer profile translated to English.
Back to original languageAbout Souleymane
Data Engineerspecialized in the design, industrialization, and reliability of data platforms in production onGCP.
I work on complex data environments to build and optimize reliable and scalable pipelines (ETL / ELT), from data ingestion to data exposure.
My work focuses on critical data team issues:
🔧 Data Engineering & Platforms
Python | SQL | Airflow | dbt | Spark | BigQuery | GCP
☁️Cloud & Data Platforms
GCP (BigQuery, Cloud Storage, Dataproc), Airflow orchestration, dbt transformations, Spark/PySpark processing
📊Objective
Build robust, maintainable, and production-ready data systems for data and business teams.
French
Native or bilingual
English
Fluent
Can work on-site
Nantes (up to 50km), Brest (up to 50km), Rennes (up to 50km), Bordeaux (up to 50km), Paris (up to 50km)
Experience
- Data For Good – BioLit / Planète MerData Engineer – Data Pipelines & Platform (Python / GCP / ML)CIVIC AND SOCIAL ORGANIZATIONSApril 2026 - Today (4 months)Nantes, FranceIndustrialization of a Data / ML pipeline for processing and analyzing images in an environmental project.🔧 Key Responsibilities:
- Design and optimization of ETL pipelines for automated image processing
- Implementation of incremental processing to reduce reprocessing times and optimize performance
- Integration of computer vision models into industrialized pipelines
- Orchestration of flows between APIs, object storage (S3 / MinIO), PostgreSQL, and Label Studio
- Improvement of processing robustness, maintainability, and scalability
- Participation in structuring Data / ML workflows to facilitate the use of annotated data
🎯 Impact:- Significant reduction in processing times
- Improved pipeline robustness and stability
- Contribution to an environmentally impactful data platform
- IMT ATLANTIQUEData Engineer – Data Platform & KPI Engineering (Python / SQL / Power BI)PUBLIC SECTORSeptember 2025 - April 2026 (7 months)Nantes, FranceAutomation of a decision-making pipeline for monitoring analytical indicators for a network of 162 engineering schools.The mission aimed to centralize, transform, and expose the data necessary for managing 4 strategic monitoring indicators, each composed of several analytical sub-categories.
- Design and development of ETL/ELT pipelines for data collection, transformation, and exposure
- Development and orchestration of workflows via Airflow
- Data transformation and modeling with DBT
- Development of data processing on Google Cloud Platform
- Implementation of ingestion flows to Cloud Storage
- Structuring and loading of analytical data into BigQuery
- Development and optimization of Python / PySpark processing to improve performance and scalability
- Structuring and ensuring the reliability of decision-making datasets used by business teams
- Implementation of data quality rules and documentation of flows
- Participation in functional scoping and validation of business indicators
- Exposure of indicators via Power BI
Results- Centralization and automation of analytical data flows
- Reduction of manual operations related to data consolidation
- Improvement of processing performance and reliability
- Structuring of analytical datasets usable for business management
Environment: Python, SQL, PySpark, ETL, Airflow, DBT, GCP (BigQuery, Cloud Storage, Dataproc), Power BI, Docker, Git, Agile Scrum - CGI FranceData Engineer – Data Platform & Industrialization (Python / SQL)CONSULTING AND AUDITSMarch 2024 - December 2024 (9 months)Nantes, FranceInvolvement in an application redesign context around a database centralizing multiple business flows.
- Analysis and optimization of an existing data processing pipeline
- Identification of issues related to integration and heterogeneity of data sources
- Structuring of a processing architecture allowing centralization of transformation rules and business logic
- Implementation of a clear separation between data ingestion, transformation, and exposure
- Development and optimization of data processing in Python and SQL
- Construction and reliability of analytical datasets for business teams
- Improvement of pipeline maintainability, robustness, and scalability
- Collaboration with business teams in an Agile environment
Results- Reduction of complexity related to multi-source flows
- Improvement of data consistency and reliability
- Facilitation of evolution and integration of new data sources
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Education
- Master 2 Econometrics and Applied StatisticsInstitut d'Administration des Entreprises, IAE de Nantes2023Master 2 Econométrie et statistique appliquée
- Statistics and Demography EngineerInstitut National Des Statistiques et Economies Appliquées2022Ingenieur Statistique et Démographie
Certifications
- Organize your work according to priorities and objectivesTalend solution
- Have team spiritTalend solution