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Build and maintain a real-time Sim Racing platform: collect race telemetry, run distributed services, and ship UIs for pilots, centers and operators using Python, React and TypeScript.
Build and maintain a connected Sim Racing platform: real-time data pipelines, distributed services, and UIs for pilots, centers, and operators using Python, React, and TypeScript.
Build high-performance Go microservices using gRPC/REST APIs, optimize concurrency, and deploy on Kubernetes while managing PostgreSQL, MongoDB, Redis, Kafka, and NATS.
Build and maintain the company’s semantic data layer, canonical models, and metric definitions to power self-serve analytics for Finance, Growth, and Operations.
Build and scale data pipelines for AI model training, integrating infrastructure, engineering, and research to create high-quality datasets.
Design and deploy cloud data platforms and pipelines on GCP/AWS/Azure, build analytics solutions, and optimize costs for enterprise clients.
Builds and maintains secure data pipelines for a sensitive government project using Python, Spark, Hadoop, and Kafka, ensuring data quality and compliance with RBAC/ABAC models.
NEOGEO, filiale de GEOFIT, recherche un Développeur Python Data/SIG (H/F) à Toulouse pour renforcer son équipe Innovation R&D. Le poste s’inscrit dans un projet France 2030 et vise à bâtir une brique technologique…
Build and maintain AWS-based data pipelines for Safran Aircraft Engines, ingesting MES/ERP/PLM and IoT feeds, transforming them in a medallion lakehouse, and enabling business teams with Power BI dashboards.
Build and maintain automated data pipelines using Snowflake and AWS services, focusing on ETL/ELT, data modeling, and cloud infrastructure with Terraform and CI/CD.
Senior Data Engineer builds cloud-native data platforms and MLOps pipelines, enabling AI/ML model deployment and analytics across AWS, GCP, and Azure.
Senior Data Engineer/ML Engineer designs, deploys, and maintains scalable ML models and MLOps pipelines for enterprise clients, using Python, SQL, Spark, and AWS.
Senior Data Engineer builds and maintains BI pipelines and reports to track portfolio performance and governance for a fintech company.
Design, deploy, and scale production ML models for enterprise clients, owning the data platform, MLOps practices, and model lifecycle governance.
Build and maintain data pipelines, warehouses, and cloud infrastructure using AWS, SQL, Spark, and Python for a client project.
Design and deploy robust AWS-based data pipelines and Lakehouse architectures for analytics and governance, integrating Snowflake and supporting GenAI/MLOps initiatives.
Design and maintain real-time data pipelines from MES/ERP systems into an AWS Lakehouse using PySpark, Redshift, and Glue, ensuring data quality and traceability.
Build predictive models and KPI dashboards using Python/R and big-data tools to drive client decisions from raw and unstructured data.
Designs and deploys Microsoft-based data pipelines and migrates BI systems to the cloud, ensuring performance, reliability, and security.
Design and deploy production-grade Data, AI, and GenAI solutions for critical environments, focusing on industrialization and monitoring in multidisciplinary teams.
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