Freelancer profile translated to English.

Description

+9 years of experience in Data Engineering & Artificial Intelligence on Google Cloud Platform.

Senior Data Engineer & freelance AI Consultant, I support large groups in industrializing their data projects and deploying generative AI solutions in production — from designing cloud architectures to commissioning conversational assistants used by 15,000 users.

Assignments carried out for major clients: Servier, Sephora, Stellantis (formerly Groupe PSA), Louis Vuitton — in pharmaceuticals, retail, automotive, and luxury.

What I bring concretely:

➤ Data Engineering: design and industrialization of data pipelines on GCP (BigQuery, Composer, Cloud Functions, Pub/Sub, Dataproc), dbt modeling, Data as a Service architectures, CI/CD, and monitoring

➤ Generative AI (GenAI): LLM pipeline design, RAG architectures, Vertex AI integration, AI API Gateway development (LangChain, LangGraph, FastAPI), vector databases (PgVector, Weaviate), Cloud Run deployment, observability via Langfuse

➤ Support & Lead: technical scoping, data & cloud architecture, industrialization, support for business and technical teams

Stack: Python, SQL, BigQuery, Cloud Run, Cloud Functions, Composer, Pub/Sub, Dataproc, Terraform, Docker, dbt, LangChain, LangGraph, Vertex AI, RAG, PgVector, Weaviate, Langfuse, FastAPI, GitLab CI/CD

5x Google Cloud Certified: Professional Data Engineer, Professional Cloud Architect, Professional Cloud Developer, Associate Cloud Engineer, Digital Leader | Dataiku Certified User

Available for a new freelance mission (Data Engineer, AI Engineer, Data Lead) in Île-de-France or full remote.

Contact:

Technical articles: cheickcisse.medium.com

Languages

French
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km)

Servier
Senior Data Engineer & AI
January 2023 - April 2026 (3 years and 3 months)
Paris, France
Within the pharmaceutical group Servier, involved in two strategic areas: the design and deployment of a Data as a Service (DaaS) platform for international subsidiaries, and the design of large-scale industrialized generative AI (GenAI) solutions.

Generative AI (GenAI):
• Design and development of LLM pipelines (RAG, LangChain, LangGraph, ADK) for creating business conversational assistants — 15,000 active users in production
• Development and maintenance of an API Gateway in Python (FastAPI) for LLM orchestration and Vertex AI integration
• Deployment and industrialization of AI services via Cloud Run (Load Balancer, auto-scaling, endpoint security) with Cloud SQL and PgVector
• Monitoring, observability, and MLOps: prompt traceability, latency metrics, and response quality via Langfuse
• Prompt engineering and continuous improvement of assistants: hallucination management, quality evaluation, user feedback

Data as a Service (DaaS) Platform:
• Design of pre-configured GCP environments to accelerate data deployment and integration for international subsidiaries
• Development and automation of ETL/ELT data pipelines (ingestion, transformation, exposure) with BigQuery, Cloud Functions, Composer, and Pub/Sub
• Industrialization of dbt models for data transformation and modeling in BigQuery
• Infrastructure as Code and CI/CD: Terraform, Docker, GitLab CI/CD with reusable templates
• Development of serverless services (Cloud Run, Cloud Functions) for the application platform
• Environment and pipeline monitoring, support for subsidiaries on cloud and data best practices
Stack: Python, SQL, FastAPI, BigQuery, Cloud Run, Cloud Functions, Composer, Pub/Sub, Cloud SQL, PgVector, Weaviate, LangChain, LangGraph, ADK, Vertex AI, Langfuse, dbt, Terraform, Docker, GitLab CI/CD
Sephora
Data Engineer
March 2021 - December 2022 (1 year and 9 months)
Paris, France
Within the Sephora group, in a context of strong growth in data activities, involved in several GCP projects to industrialize the management of data related to Employee solutions (Finance, Retail, non-European countries).

Data Engineering & Pipelines:
• Development and automation of ingestion and transformation data pipelines on GCP (BigQuery, Cloud Functions, Composer, Pub/Sub)
• Design of PoCs and scalable data architectures for the analytical needs of business teams
• Industrialization of data transformation models in BigQuery with Python and SQL
• Implementation of unit, E2E, and TNR tests to ensure pipeline reliability in production

Machine Learning & Cloud:
• Deployment and integration of Machine Learning models with Dataiku and BigQuery ML
• Design and deployment of Cloud architectures on Google Cloud Platform
• Implementation of monitoring solutions and CI/CD chains (GitLab CI, Terraform)
Stack: Python, SQL, BigQuery, Cloud Functions, Composer, Pub/Sub, Dataiku, BigQuery ML, Terraform, GitLab CI/CD, GCP
Sephora
Data Engineer
RETAIL (SMALL BUSINESS)
March 2021 - January 2023 (1 year and 10 months)
Paris, France
Within the Sephora group, in a context of strong growth in data activities, involved in several GCP projects to industrialize the management of data related to Employee solutions (Finance, Retail, non-European countries).

Data Engineering & Pipelines:

- Development and automation of ingestion and transformation data pipelines on GCP (BigQuery, Cloud Functions, Composer, Pub/Sub)
- Design of PoCs and scalable data architectures for the analytical needs of business teams
- Industrialization of data transformation models in BigQuery with Python and SQL
- Implementation of unit, E2E, and TNR tests to ensure pipeline reliability in production

Machine Learning & Cloud:

- Deployment and integration of Machine Learning models with Dataiku and BigQuery ML
- Design and deployment of Cloud architectures on Google Cloud Platform
- Implementation of monitoring solutions and CI/CD chains (GitLab CI, Terraform)

Stack: Python, SQL, BigQuery, Cloud Functions, Composer, Pub/Sub, Dataiku, BigQuery ML, Terraform, GitLab CI/CD, GCP
Google Cloud Platform Composer Python Docker Dataiku