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Build and optimize robust, scalable data pipelines and architectures for enterprise clients, blending hands-on engineering with consulting to turn business needs into actionable data solutions.
Lead a team of Data Engineers to design and deliver cloud-native data platforms and AI solutions for global clients, using Python, Spark, Airflow, and major cloud platforms (GCP, AWS, Azure).
Senior ML Engineer builds and maintains data pipelines and ML models in production for a French insurer, owning the full MVP lifecycle from ideation to deployment.
Build and maintain scalable data pipelines and predictive models for payment flows using GCP, MLOps, and AI/ML in a fintech setting.
Build and deploy MLOps pipelines to collect robotics data, orchestrate model training, and automate deployment for AI-driven warehouse automation systems using Python, cloud infra, and Kubernetes.
Build and maintain scalable data pipelines and architectures to feed AI/ML models, ensuring data quality and enabling automated model training and deployment.
Designs and builds scalable data pipelines in Python, SQL, dbt and Airflow, manages cloud data warehouses (BigQuery, Snowflake, Databricks), and explores generative AI to automate workflows for enterprise clients.
Build and maintain a petabyte-scale data platform for an AI-safety startup, designing storage, APIs, and governance to support LLM/VLM training and millions of daily API calls.
Design and build scalable cloud data architectures (Snowflake, GCP/AWS/Azure) and robust ETL pipelines, then expose clean, governed data to analytics and AI teams using dbt and modern data-stack patterns.
Administer and optimize the Dataiku platform, support data scientists, and coordinate with vendors and stakeholders while ensuring MLOps and DevSecOps best practices.
Builds and maintains data pipelines and ML infrastructure to power pricing, sales, and inventory optimization models for HP’s commercial teams using Python, Spark, and SQL.
Design and build scalable data pipelines and GenAI platforms on AWS, using Spark and modern data architecture to support analytics, AI, and Generative AI use cases.
Build and maintain a Microsoft Fabric-based data platform for a multi-energy provider, focusing on ingestion, lakehouse architecture, and data quality.
Lead a team to design and build scalable data pipelines and platforms for clients, advising on cloud and big-data tech while enforcing DevOps, FinOps, and governance best practices.
Lead a small team to design and deliver Snowflake-based data pipelines and AI workflows for Sanofi, using DBT, Airflow, Python, and AWS to scale GenAI and agentic AI systems across a global biopharma enterprise.
Build and maintain scalable data pipelines and ETL processes to power AI model training and analytics at a cutting-edge AI company.
Build and maintain scalable data pipelines and models (Snowflake, dbt, Airflow) to power analytics, reporting, and AI use cases for a global enterprise integration platform.
Designs and maintains scalable ETL/ELT pipelines and cloud data infrastructure to support analytics and ML workflows in a French HR-tech environment.
Build and deploy ML models in production, automate pipelines, and manage cloud infrastructure for a digital marketing company.
Build and maintain scalable MLOps and DevOps infrastructure to deploy, monitor, and scale ML/AI models in production for a digital marketing platform.
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