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Build and maintain scalable data pipelines and systems for a geolocation analytics platform, integrating diverse datasets and optimizing big-data infrastructure.
Build and maintain data pipelines and cloud-based data platforms for clients using Python, SQL, Docker, Kubernetes, and Terraform across GCP, Azure, and AWS.
Build and optimize cloud data pipelines using DBT, SQL, and CI/CD in a modern data stack (Snowflake/BigQuery/Redshift) for a product company.
Build and optimize GCP-based data pipelines and vector databases to power AI models like LLMs and RAG systems for Doctolib’s AI Medical Companion, supporting healthcare professionals across Europe.
Build and maintain scalable data pipelines and infrastructure for a media company using Python, Spark, BigQuery, and GCP.
Builds scalable data pipelines in Python on GCP, models Snowflake warehouses, and integrates multi-source data for analytics and reporting.
Builds and maintains the backend services and AI pipelines for an enterprise-grade conversational AI agent using Python, FastAPI/Flask, LangChain, and Google Gemini Enterprise on GCP.
Build and maintain scalable data pipelines and BI infrastructure on GCP (BigQuery), using dbt and Trino to feed MicroStrategy dashboards and enable AI-driven insights.
Build and maintain Nutripure’s data platform on GCP, ensuring reliable, fresh data pipelines and enabling analysts with clean models and observability.
Build and optimize cloud data pipelines on GCP for enterprise clients, designing scalable architectures, auditing existing systems, and implementing data ingestion/transformation solutions using Python, Scala, and SQL.
Builds and maintains backend services and AI pipelines for conversational agents using Python/Go, integrating LLM APIs (Gemini/Vertex) and social data sources to power Ipsos Synthesio’s social intelligence platform.
Senior Data Engineer designs and builds scalable data platforms (data lakes, warehouses, pipelines) for clients, using cloud tools (GCP/Azure), ETL/ELT (dbt, Snowflake), SQL and Python to deliver reliable, high-performance data solutions.
Build and deploy AI-powered data pipelines and ML models for client marketing analytics using Python, Airflow, and BigQuery, then visualize insights in Power BI or Looker.
Build and maintain data pipelines, data marts in BigQuery with DBT, and dashboards in Tableau to power healthcare insights and AI strategy at a leading health-tech company.
Build and maintain data pipelines in Python (Dagster) and SQL/Jinja (DBT) to power analytics and AI at Doctolib, a healthcare platform.
Design and build cloud data platforms on Snowflake and AWS/Azure/GCP, model data, write ETL/ELT pipelines, and advise clients on data architecture and best practices.
Build and optimize a new GCP-based data platform for a large French fresh-food retailer, focusing on ingestion pipelines, performance tuning, and FinOps while migrating from legacy systems.
Designs and maintains scalable GCP data pipelines (BigQuery, Dataflow, Dataproc) for retail clients, automating data flows and optimizing analytics infrastructure.
Senior Data Engineer builds and governs robust data pipelines and architectures for AI agents in finance, public sector, luxury, and healthcare, ensuring reliability and scalability for production use.
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