Freelancer profile translated to English.
Back to original languageAbout Youness
Senior Data & AI Engineer with 7 years of experience in designing, industrializing, and architecting cloud-native and on-prem data platforms. Expert in cloud architecture, data warehousing, ETL, and Generative AI, I manage end-to-end solutions—from event ingestion to analytical pipelines to production RAG chains. Solid experience collaborating with cross-functional teams to deliver high-value data architectures. Available for freelance, I work as a Lead Data Engineer or Data Architect on high-impact projects: cloud migration, data platform, Generative AI, and MLOps.
✥ Certified :
▸ GCP Generative AI Leader
▸ GCP Professional Cloud Architect
▸ GCP Professional Data Engineer
▸ Terraform Associate
▸ Azure Data Scientist Associate
▸ Azure Data Engineer Associate
▸ Professional Scrum Master PSM I
French
Native or bilingual
English
Fluent
Arabic
Native or bilingual
Can work on-site
Paris (up to 50km)
Experience
- ORANGELead Data Engineer & ArchitectDIGITAL AND ITNovember 2024 - Today (1 year and 9 months)Paris, FranceBuild/Run of Data and Generative AI products within the Data-IA IT department of Orange France. Dual role Architect + Lead Engineer: design of target GCP architectures, solution selection, security/compliance, FinOps, and technical leadership on 4 products (Carbone, Blueprint, AsTer, Release Management Assistant, Public Cloud) as well as the on-prem Secu360 project as tech lead.Achievements :
- Standardized Architecture & DataOps : Design of GCP architectures (batch, event-driven, micro-services), component selection, SLO/SLA, IAM compliance and FinOps. Industrialization via reusable templates (dbt, Dataflow, APIs), GitLab/Cloud Build CI/CD and Terraform IaC.
- GCP Pipelines and Analytics : Ingestion and transformations on BigQuery with dbt, GCS/Pub/Sub, reliable data marts for DataViz. Exposure and feeding of Power BI (AsTer). Result: reduced time-to-prod and enhanced performance/quality.
- Generative AI & RAG (AsTer, Release Management) : Design of RAG chains with LangChain, embeddings, and AlloyDB vector index; prompting, traceability, and observability. 2025 MVP objective: ~30% gain in impact analysis and test planning.
- Secu360 on-prem (tech lead) : Architecture and development of Spark processing on Hadoop (Hive/HDFS/HBase), Oozie orchestration, security dashboards. Results: improved patching velocity and increased SOC team efficiency.
Technical Environment : GCP: BigQuery · Cloud Run · Cloud Functions · Workflows · Pub/Sub · AlloyDB · Vertex AI · Firestore | On-prem: Scala/Spark · Hadoop · Hive · HDFS · HBase · Oozie · Jenkins | dbt · Python · SQL · LangChain · Docker · GitLab CI · Cloud Build · Terraform - L'Oréal SA - L'Oréal FranceLead Data EngineerFASHION AND COSMETICSOctober 2022 - October 2024 (1 year and 11 months)Paris, FranceRedesign and migration of data pipelines feeding over 60 retail and digital marketing dashboards (GA, Traackr, Meta…) used by over 4,000 users worldwide, from DOMO to GCP and Power BI. Management of L'Oréal's and its partners' customer data, as well as sales activation. Team of 12 people (3 POs, 1 Scrum Master, 1 tech lead, 5 data engineers, 2 data viz).Achievements :
- GCP Infrastructure & CI/CD : Setup of GCP infrastructure and configuration of CI/CD pipelines on GitHub.
- Modeling & DataViz : Collaboration with the DataViz team in data modeling to create optimized and relevant dashboards.
- Business KPIs : Design and development of key KPIs in collaboration with business teams (Conversion Rate, CLV, Avg. Sales…).
- Multi-source ETL : Development of ETL to extract data from various sources (APIs, SAP, etc.) and data transformations.
- Event-driven Pipelines : Development of event-driven pipelines for fast, real-time data integration.
- Architecture & Innovation : Active contribution to architecture improvement, providing innovative solutions to optimize performance.
- Agile Management : Creation of technical user stories, backlog management, and estimation, enabling efficient project planning.
- Documentation : Writing technical and functional documentation to ensure the smooth operation of the project.
Technical Environment : GCP: BigQuery · Cloud Run · Cloud Functions · Cloud Build · Workflows · Airflow · Pub/Sub | SQL · Python · Terraform · GitHub · Docker · Kafka - ORANGEData EngineerDIGITAL AND ITDecember 2020 - October 2022 (1 year and 10 months)Paris, FranceMigration and development of several Data projects within the Orange IT department to meet internal client needs (customer knowledge, IoT, servers, network, security…). Team of 14 people (3 POs, 1 architect, 2 tech leads, 8 data engineers).Achievements :
- ETL Migration : Redesign and migration of On-Prem ETL (Hadoop) to GCP (Dataflow, GCS, BigQuery).
- MLOps / Vertex AI : Support for Data Scientist teams in deploying their models on GCP with Vertex AI.
- KPIs & Metrics : Development of new metrics and KPIs (5G, Livebox, Security, etc.).
- Maintenance & Evolution : Maintenance and evolution of existing project functionalities.
- CI/CD : Implementation of CI/CD pipelines.
- Monitoring : Creation of monitoring dashboards and implementation of alerting strategies.
- Documentation : Writing technical specifications and documentation.
Technical Environment : GCP: BigQuery · Dataflow · Cloud Run · Cloud Functions · Airflow · Vertex AI · BigTable | On-prem: Spark · Hadoop · Oozie · Hive · HBase · Cassandra | Java · Scala · Python · Jenkins · Git · Terraform
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Education
- Engineering Degree, Computer ScienceUniversité de Technologie de Belfort-Montbéliard2019Diplôme d'ingénieur, Informatique
- University Diploma in Technology, Computer ScienceEcole Nationale des Sciences Appliquées de Berrechid2016Diplôme Universitaire de Technologie, Informatique
Certifications
- Professional Data EngineerGoogle Cloud2021
- Azure Data Engineer AssociateMicrosoft2020