Youness Faklak

Your data platform should create value, not just cost money: and your GenAI ideas deserve to reach production, not die as slides.

Data Engineer & Cloud Architect, 10+ years building and industrializing large-scale data platforms. I help teams turn fragile pipelines into reliable Data Products, and turn "we should try AI" into working prototypes that prove their business value.

What sets me apart: I cover both ends of the chain. Heavy-duty data engineering (Databricks, Spark/PySpark, Kafka, Delta Lake, Unity Catalog, Azure) and production-grade Generative AI (RAG, AI agents, LangChain, Azure OpenAI, vector databases). Few freelancers deliver from raw data ingestion all the way to AI-powered value.

A few concrete results from large-scale environments (energy, telecom, legaltech: EDF, ENEDIS, Orange, Bouygues, LexisNexis):

Kafka & Lakehouse in production: designed secured streaming pipelines (mTLS, ACLs) and solved hard throughput limits and ingestion bottlenecks.

Performance & data quality: cut ingestion processing time by ~55% by re-engineering the load strategy, and eliminated double-counting and consistency bugs across Bronze/Silver/Gold layers.

Governance & compliance: implemented GDPR data masking and group-based access control with Unity Catalog.

Generative AI: delivered a production RAG architecture (LangChain, GPT-4, Qdrant) turning internal documents into a usable assistant.

I work on fixed-scope engagements:

→ GenAI POC: a RAG or AI agent on your own data, delivered and demonstrable, to validate a use case fast.

→ Data architecture audit: an external review of your Databricks/Lakehouse stack with an actionable roadmap (performance, cost, governance).

→ Pipeline design & industrialization: modeling, quality, monitoring, production rollout.

Tell me your business problem in a few lines. I'll come back with a clear first read of your needs and a concrete way to scope it.

Bilingual FR/EN: available for remote missions.