Method, field & CV
AI & Data Engineer with 4 years of experience, focused on designing data and AI architectures: ELT/ETL pipelines, BigQuery modeling, Cloud Run, RAG, agent workflows, automation, and scalable delivery—with strong software engineering and DevOps discipline. Impact-driven, performance-aware, and focused on business adoption.
We design and ship AI systems that move from prototype to production.
Beyond one-off POCs, we build scalable, orchestrated, production-grade systems wired into real business workflows.
Our job is to turn use cases from slides into real services: trustworthy data, stable APIs, useful interfaces, and observable AI once it’s live.
We work across the full arc — business framing, architecture (RAG, agents, data platforms), implementation, and industrialization (Cloud Run, CI/CD, quality).
We start by clarifying the workflow: who decides with what, which dataset is the source of truth, and what “good” looks like in practice.
We prefer testable increments: small releases, visible metrics, and technical debt surfaced early.
We document and hand over: a deliverable without transfer doesn’t create lasting value for the team.
We’ve shipped in demanding settings: consulting & innovation (Axys), retail & finance (Carrefour), automotive (Škoda), postal and mobility (La Poste, SNCF, Air France).
Those contexts trained us for month-end pressure, sensitive data, and the trade-offs between analytical rigor and product speed.
AI side: LangChain, LangGraph, MCP, multi-vendor LLMs (OpenAI, Gemini, Vertex AI).
Data & platform: Python, SQL, BigQuery, GCP, Terraform, Docker, GitHub Actions.
We keep a steady eye on agents and LLMOps — to recommend durable technical choices, not only what’s trending.
Making AI actionable: systems embedded in workflows, measurable, and maintainable — not just isolated demos.
If you have a data, AI, or industrialization topic, reach out — we reply quickly to structured messages.
AI/LLM Engineer — RAG Architect
Data Engineer — Finance Transformation (ERP migration)
During the PeopleSoft-to-SAP S/4HANA ERP migration, contributed to accounting discrepancy stabilization and intercompany finance flow reliability.
Tech stack BigQuery · SQL · Looker · SAP · Dataplex
Machine Learning Engineer — Marketing Analytics
Predictive marketing initiative focused on audience segmentation, campaign targeting, and media efficiency.
Tech stack Vertex AI · BigQuery ML · Python · SQL
BI Analyst — Accounting Transformation
Supported the national accounting leadership to industrialize reporting and improve transformation program steering.
Tech stack Power BI · DAX · Power Query
BI Analyst — Safety & Environmental Performance
Within SNCF Réseau's DIPR division, designed safety/environment steering tools for operations and risk prevention.
Tech stack Power BI · DAX · Power Query · REST API · Excel VBA · VB.Net
BI Analyst — Route Economics Optimization
Mission focused on route profitability optimization through modernization of economic steering analytics.
Tech stack Python · SQL · Flask · SAP BW · Business Objects · VBA
A concise view of technical and interpersonal skills we rely on in delivery work.
Languages, tooling, cloud and production practices — the backbone of our data & AI deliverables.
Professional posture and teamwork to clarify needs, protect quality, and make outcomes actionable.
Technologies and tools we use often — not exhaustive; aligned with projects and CV (Shields.io badges).
Certifications on LinkedIn — full, up-to-date list.
Data engineering, data science & analysis
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