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Build and optimize data pipelines on AWS for clients, focusing on automation, Spark, and CI/CD to enable scalable analytics and business insights.
Lead a team building robust data pipelines on Databricks, using Spark, Python and SQL to migrate and industrialize a new data platform.
Build and maintain high-performance data pipelines using Scala and Spark, migrating legacy Hadoop systems to Snowflake for Groupe Open’s Open Data & AI unit.
Build and maintain data pipelines in Python and Airflow, automate cloud workflows on AWS, and integrate generative AI models as part of a data engineering team.
Lead a renewable-energy data platform, set technical standards, build reliable pipelines, and ensure data quality and observability for Akuo’s Paris-based team.
Build and industrialize data pipelines, design business models, and ensure data quality for an international team.
Builds backend services and LLM pipelines for an AI-powered conversational agent using Python, REST APIs, and GCP in an agile team.
Designs and maintains scalable data pipelines and models for AI and BI use, working in autonomous squads to ensure data quality and observability.
Builds and maintains backend pipelines and services that run quantitative risk models in production, focusing on performance and explainability while collaborating with data, product, and business teams.
Build, scale, and maintain ML models and data pipelines for a growing AI product team in Paris.
Design and deploy Azure cloud and AI pipelines, integrating Kafka and LangChain while automating data flows for scalability.
Designs and builds data pipelines, warehouses, and aggregations on Teradata and Big Data platforms, automating workflows with DevOps and CI/CD for a bank’s analytics team.
Build and maintain data pipelines and dashboards for a 10k+ employee company, collaborating with data scientists and DevOps to ensure data quality and insights delivery.
Build and deploy AI applications using large language models and data pipelines in small teams, occasionally leading projects and advising clients on AI solutions.
Build and maintain cloud data pipelines and analytics for banking/insurance clients using Spark, Kafka, AWS, and Python, with a focus on data quality and risk/finance reporting.
Industrialize AI models and data pipelines for a large bank’s AI Center of Excellence, implementing MLOps, LLMOps, and CI/CD while ensuring security and observability.
Build and maintain robust data pipelines using SQL, dbt, and cloud data warehouses like Snowflake or BigQuery to make business data accessible and reliable.
Build and maintain robust data models and pipelines using SQL, dbt, and cloud warehouses (Snowflake/BigQuery/Databricks) to power business decisions.
Design and maintain scalable data pipelines and architectures (ETL/ELT, data lakes, warehouses) using Python, SQL, Spark, Kafka, and cloud platforms (AWS/GCP/Azure).
Designs and runs Azure-based big-data pipelines using Spark, Hadoop, and Azure services to ingest, process, and store data for analytics and AI projects.
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