Freelancer profile translated to English.
Back to original languageAbout Ryan
I help Data teams build, validate, and industrialize their pipelines on Azure Databricks.
My main topics: PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Factory, Azure DevOps, CI/CD, monitoring, Spark optimization, and data governance.
I can assist with:
– building or redesigning batch / near-real-time pipelines;
– Databricks / Unity Catalog migration or structuring;
– optimizing Spark job performance/costs;
– implementing tests, monitoring, alerting, and runbooks;
– industrializing ML models with MLflow/MLOps;
– GenAI/RAG use cases when data needs to be properly prepared, governed, and put into production.
Experience in finance / banking environments: SIX, BNP Paribas CIB, Banque de France.
Stack: Azure, Databricks, AWS, PySpark, SQL, Python, Delta Lake, Unity Catalog, ADF, Azure DevOps, MLflow, Scikit-learn, Pandas.
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 50km)
Experience
- SIXData Cloud Engineer & ScientistSeptember 2024 - Today (1 year and 11 months)Paris, FranceData Cloud Engineer & Scientist — SIXSeptember 2024 – PresentWorking on data engineering, cloud data platform, and AI industrialization in a finance environment.Key achievements:– Building batch / near-real-time pipelines on Azure Databricks with PySpark, SQL, and Delta Lake.– Industrializing billing Spark jobs: business rules, tests, monitoring, alerting, and documentation.– Optimizing cloud processing: partitioning, schemas, orchestration, performance, and costs.– Contributing to Unity Catalog governance: permissions, naming standards, traceability, and space structuring.– Implementing CI/CD practices with Azure DevOps, Databricks Jobs, and Azure Data Factory.– MLOps work: MLflow tracking/registry, packaging, deployment, and drift monitoring.Deliverables: production pipelines, industrialized Databricks jobs, Unity Catalog repository, CI/CD pipelines, documentation, and runbooks.Stack: Azure, Databricks, PySpark, SQL, Python, Delta Lake, Unity Catalog, ADF, Azure DevOps, MLflow.
- BNP Paribas CIBPython/SQL DeveloperSeptember 2022 - September 2024 (2 years)Paris, FranceOptimized SQL stored procedures (exposure calculations, cash flow projections), execution plans, indexing.Python/SQL automation of multi-source ingestions (files, databases), integrity checks, and data cleansing.CSV/Excel production for reporting, detection of historical inconsistencies (business rules + statistical checks).Early repayment ML projects: EDA, feature engineering, validation (cross-validation, anti-leakage guardrails), MLP / RandomForest training, F1/AUC monitoring.Daily Qlik Sense dashboards (risk KPIs, operational views, ad hoc analyses), rapid iterations with business stakeholders.
- BANQUE DE FRANCESoftware DeveloperMay 2022 - July 2022 (2 months)Paris, FranceDigitalization of billing & reporting processes: transition from manual to automated.Billing application under Excel/VBA: user interfaces, input validation, document generation, payment tracking.Quality & traceability: validation rules, archiving, operation logging.Standardization of Excel templates (structures, names, tabs) to facilitate maintenance and future analysis.Transfer & documentation: user guide, handover to teams.Key deliverables: ready-to-use application, standardized templates, operating procedures.Stack: Excel/VBA (UserForms), macros, file management.
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Education
- Master AI & BigDataESGIFormation en alternance axée sur la data science, le data engineering et l'industrialisation IA/Big Data en environnement cloud. Compétences acquises : Deep Learning, NLP, Machine Learning supervisé et non supervisé, Spark (Core / Streaming), Kafka, conteneurisation (Docker/Kubernetes), CI/CD, cloud computing (Azure/GCP), sécurisation et orchestration de projets IA. Mise en œuvre de solutions industrielles de traitement, d’analyse et de valorisation de données massives en contexte métier.
- Bachelor - Software Application Development ManagerESGI2024Formation en alternance spécialisée en développement logiciel, bases de données et Big Data. Compétences acquises : développement en Python, Java et C, SQL avancé, conception de bases relationnelles et NoSQL, introduction au Machine Learning, intégration et transformation de données massives. Approche projet (gestion agile, industrialisation) et forte sensibilisation aux bonnes pratiques de code et d'optimisation logicielle.