Freelancer profile translated to English.
Back to original languageAbout Soufiane
Data engineer with solid experience in production environments, I help companies build reliable, scalable, and AI-ready data architectures.
My optimizations on data pipelines have reduced costs by several hundred thousand euros in production. This is what I bring to each mission: a rigorous technical vision, focused on performance and real business impact.
I work across the entire data chain: ETL/ELT pipeline design, orchestration, modeling, and data quality assurance. I have worked on complex, large-scale data projects, particularly on enterprise platforms like Palantir Foundry.
My differentiating asset: coming from a Master's in Data Science, I understand the needs of ML and AI teams upstream. I build pipelines designed for real-world use—feature stores, training data, monitoring—without data scientists having to rework them.
Key Skills:
— Data Engineering: Python, Spark, SQL, ETL/ELT, orchestration
— Platforms: Palantir Foundry, Databricks
- Cloud: GCP, AWS
— MLOps: Data CI/CD, model deployment, monitoring
— AI: LLM integration, RAG pipelines, data for AI agents
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 50km)
Experience
- Société GénéraleData EngineerBANKING AND INSURANCESeptember 2023 - Today (2 years and 9 months)La Défense, FranceAs part of this long-term assignment, I act as a Data Engineer in a large-scale production environment.Key achievements:→ Optimization of the data infrastructure, generating several hundred thousand euros in savings through the redesign of underperforming Spark pipelines and significant reduction in processing times and compute costs.→ Design and development of scalable data pipelines (ETL/ELT) on Palantir Foundry, ensuring reliability and maintainability in production.→ Optimization of Big Data workflows under Apache Spark and Python: reduction of execution times, improved memory management, and data partitioning.→ Implementation of automated data quality control processes, reducing manual interventions and production errors.→ Close collaboration with Data Science teams to provide reliable, documented, and reusable datasets, accelerating the production deployment of ML models.→ Contribution to the overall data architecture with a focus on scalability, performance, and infrastructure cost reduction.Technical environment: Palantir Foundry, Apache Spark, Python, SQL, ETL/ELT, Big Data, MLOps, Data Quality, Pipeline Orchestration.
- Societe GeneraleData ScientistBANKING AND INSURANCEMarch 2023 - September 2023 (6 months)Paris, FranceAs part of my end-of-studies internship (Master's in Data Science), I worked on a synthetic data generation project, a topic at the intersection of data science, data privacy, and dataset quality.Key achievements:→ Design and development of a synthetic data generation engine capable of reproducing the statistical distributions of real data while ensuring the confidentiality and security of sensitive data.→ Application of advanced Machine Learning and statistical modeling techniques to generate realistic artificial datasets, usable for testing and analysis phases without exposing personal data.→ Implementation of an evaluation framework for synthetic data quality: similarity measurement, statistical fidelity metrics, and usability tests to ensure the reliability of generated datasets.→ Integration of the generation pipeline into the company's internal testing environment, with complete technical documentation facilitating adoption by teams.Impact: Reduced reliance on real data for testing phases, accelerated development cycles, and enhanced compliance with GDPR / Privacy by Design requirements.Technical environment: Python, Airflow, Jenkins, Docker, Git, Machine Learning, Statistical Modeling, Synthetic Data Generation, Data Privacy, Data Quality, GDPR, Pandas, Scikit-learn.
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Education
- Double Degree MSIAM Data ScienceENSIMAG2023
- EngineerENSIMAG - Grenoble INP2023
Certifications
- Certified Palantir Foundry Data Engineer ProfessionalPalantir2025
- Databricks Certified Data Engineer AssociateDatabricks2026