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Data Platform Engineer
Build and champion a data platform on AWS (S3, EMR, Glue, Athena) to support pipelines and analytics, while coaching teams on best practices and tooling.
Data engineer / IA – Domaine électronique (H/F)
Build and maintain scalable AWS-based data pipelines for semiconductor analytics, feeding forecasting models and ML use cases while collaborating with design, IT, and finance teams.
Data engineer GCP - Secteur Retail (H/F)
Designs and maintains scalable GCP data pipelines (BigQuery, Dataflow, Dataproc) for retail clients, automating data flows and optimizing analytics infrastructure.
Consultant.e Senior Data Engineer AWS H/F
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.
Data Engineer - MLOps Engineer F/H
Build and maintain ML pipelines for banking use-cases, deploy models to production, and monitor performance using Python, Spark, Kubernetes, and AWS SageMaker.
Lead Data Engineer (H/F) (IT) / Freelance
Lead Data Engineer builds and runs a global cloud-native data platform (Databricks lakehouse, AWS) for a B2C energy company, owning architecture, pipelines, and DataOps while integrating AI tools to accelerate delivery.
Senior Python Data Engineer — Energy Optimization
Senior Python engineer building scalable data pipelines and applications to modernize energy-sector systems using Python, Pandas, and DevOps practices.
Senior Cloud Data Engineer (H/F)
Build and maintain cloud-based data platforms (datalakes, ETL pipelines) for enterprise clients, using AWS/GCP/Azure, Python, Airflow, and DevOps tools.
Data Engineer Python/AWS (F/H)
Build and maintain distributed data pipelines and cloud services using Python, PySpark, and AWS (Glue, Lambda, ECS) to deliver reliable, high-performance data APIs and integrations.
Consultant.e Data Engineer AWS H/F
Build and optimize data pipelines on AWS for clients, focusing on automation, Spark, and CI/CD to enable scalable analytics and business insights.
Data Engineer / Data Analyst confirmé à expert (F/H)
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.
Data Engineer F/H H/F
Build and maintain robust data pipelines on AWS to centralize and process terabytes of media audience, adserver, CRM, and radio data, using Python, PySpark, and SQL to deliver actionable insights and KPIs for advertising, streaming, and CRM teams.
Data Engineer Informatica IDMC (H/F)
Build and maintain robust data pipelines and warehouses using Informatica IDMC, Python, SQL, and Google Cloud, enabling analytics and future AI models for a cooperative sector leader.
Stagiaire Data engineer - Products Data (H/F)
Build and maintain data pipelines for AI-driven SaaS products (DemandSens, Sellia) using Airflow, Python, and cloud services (AWS/Azure) to power predictive analytics and sales forecasting.
Data Engineer - Modélisation & Études Irve
Builds data pipelines and predictive models for EV-charging infrastructure in collective housing, analyzing consumption patterns and optimizing grid impact using Python, Spark, and PostgreSQL.
TRACFIN - Data engineer H/F
Build and maintain data pipelines, optimize databases, and deploy data platforms for a French financial-intelligence service, using Python, SQL, and cloud-native tools.
Data Engineer (H/F)
Build and maintain data pipelines and warehouses (Snowflake, dbt, Python) to turn raw business data into analytics-ready models that power reporting and decision-making.
Data Engineer (H/F)
Build and maintain data pipelines and transformations for a SaaS platform serving automotive manufacturers and dealers, using dbt, Python, SQL, AWS S3/Redshift, and Parquet.
Senior Data Engineer
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.
Stage Data Engineer
Build and automate an end-to-end data pipeline for a new startup, cleaning, transforming, and preparing data for production using Python, SQL, and modern tooling.