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Designs and implements large-scale data solutions using Spark, Kafka, and cloud platforms to manage, analyze, and visualize data for business intelligence projects.
Build and maintain AWS-based data lakes, pipelines, and serverless ETL workflows for analytics and ML models.
Designs and builds cloud-native data platforms on Azure to process raw data into actionable insights for analytics and ML, ensuring security, scalability, and reliability.
Designs and builds scalable data pipelines on GCP to enable business decisions, focusing on security, compliance, and reliable data delivery.
Build and own secure, production-grade full-stack systems and AI agent platforms in Python/TypeScript, deploying on GCP/Kubernetes to support clinical R&D and corporate workflows in a regulated biotech environment.
Designs and builds scalable data pipelines for fraud detection, cancer research, and national intelligence projects, collaborating with analysts and engineers to process diverse data sources.
Builds and maintains Azure-based data pipelines and lake loading for analytics and ML, collaborating with analysts and architects to deliver cloud-native solutions.
Builds and owns full-stack features (frontend with React/TypeScript, backend with PHP) in a microservices architecture with AI integration, collaborating with product, design, and QA teams.
Designs and maintains full-stack applications with REST microservices in C# and Angular frontends, collaborating in Agile/Scrum teams to deliver high-quality software solutions.
Designs and builds Azure-based data pipelines to ingest, clean, and load data for analytics and ML, collaborating with data scientists and architects.
Builds and optimizes Big Data pipelines using Spark/Kafka in cloud environments, collaborating with cross-functional teams to design, implement, and estimate complex data solutions.
Come Data Engineer all'interno della practice Data Analytics , avrai modo di lavorare alla progettazione e realizzazione di soluzioni dati moderne nell'ecosistema Microsoft Fabric e Azure , interfacciandosi con…
Designs and implements complex Big Data solutions using Spark, Kafka, NoSQL, and SQL, collaborating with development teams, project managers, and clients in a multinational environment.
Develops full-stack Java/Angular applications for a global workforce management client, focusing on microservices, OCR, and performance/UX optimization in a hybrid Rome-based role.
The Azure Data Engineer will bridge data science and engineering by managing data acquisition, transformation, and loading into data lakes for analytics and machine learning. The role involves working in a cloud-native environment using Azure services, Spark, and Databricks.
Designs and builds Azure-based data pipelines and lake loading for analytics and ML, collaborating with analysts and architects in a cloud-native environment.
Designs cloud-native data pipelines and analytics solutions using Azure/Spark tools to bridge data science and engineering teams, translating business use cases into scalable data architectures.
Designs and builds scalable, secure real-time data pipelines on GCP, transforming raw data into actionable insights using Java/Scala/Python and BigQuery.
Lead a small data engineering team to design, build, and scale WeRoad’s cloud-based data platform (BigQuery, dbt, Airflow) for travel experiences, focusing on real-time pipelines, self-service BI, and AI-driven insights across global markets.
The Data Architect designs and builds large-scale batch and real-time data pipelines on the Google Cloud Platform. The role involves managing data processing systems, ensuring security and scalability, and collaborating with business partners to drive data-driven insights.
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