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Design and maintain high-volume IoT data pipelines on AWS, combining real-time and batch processing with Spark/Flink, and expose analytics-ready APIs in Python.
Build and refine BI dashboards, consolidate data pipelines, and automate reporting on GCP/BigQuery to track furniture and construction waste recycling KPIs.
Senior Data Engineer builds and optimizes large-scale data pipelines and cloud-based Big Data platforms for a major bank, using Spark, Scala, Python, and cloud tools like GCP/AWS/Azure.
Build and automate data pipelines on GCP for banking clients, using BigQuery, Spark, Airflow, and Kubernetes to process and orchestrate financial data at scale.
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 scalable data platforms and ML pipelines using Python, SQL, and cloud services like Airflow for AI-driven clients.
Build and maintain data pipelines using dbt and Snowflake, orchestrate workflows with Airflow, and automate tasks in Python for clients in finance, healthcare, mobility, and climate sectors.
Leads data-architecture and engineering projects for banks and insurers, building modern data platforms (lakes, warehouses, cloud-native) and scalable pipelines to support analytics and operations.
Build and maintain Alan’s full-stack data infrastructure—from SQL/Python pipelines and Snowflake warehousing to Metabase dashboards—helping the company use data to improve health insurance, prevention, and member care.
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.
Senior Data Engineer builds and runs AWS-based data pipelines, mentors junior engineers, and advises clients on scalable data platforms using Python, Spark, and Airflow.
Senior Data Engineer builds end-to-end data pipelines, modern data warehouses, and BI solutions for clients in marketing, CRM, and e-commerce using cloud DWHs, dbt, Airflow, and SQL.
Data Engineer builds and maintains Snowflake/Airflow pipelines, structures data zones, and applies CI/CD standards for a government data/IA squad in Bordeaux.
Build and maintain scalable ETL/ELT pipelines on Google Cloud Platform using BigQuery, DBT, and Airflow to deliver clean, documented datasets for analytics and marketing teams.
Build and maintain scalable ETL/ELT pipelines on GCP to feed a modern data platform, enabling analytics and dashboards for an e-commerce and natural-cosmetics retailer.
Designs and builds modern data platforms using Snowflake and Airflow, transforming data pipelines in an agile team.
Build and maintain high-volume data pipelines on GCP using BigQuery, dbt, and Airflow, optimizing performance and ensuring data quality for analytics.
Design and deploy robust ETL/ELT pipelines, orchestrate workflows with Airflow, and build modern data stacks on Denodo, Dremio, Trino, and Iceberg in Kubernetes environments for public-sector clients.
Build and deploy ML models end-to-end: design MLOps pipelines, containerize services, and scale AI systems on cloud platforms like AWS/GCP.
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