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The AWS Data Architect designs and implements scalable data lake architectures and pipelines using AWS native services. The role bridges data science and data engineering to support customer data platform projects.
Manage the full data lifecycle and build BI solutions supporting strategic decisions, using SQL, Python, Power BI/Qlik, Azure Data Factory, and Snowflake within an international industrial company.
Azure Data Engineer bridging Data Science and Data Engineering, building data pipelines and loading data into data lakes for analytics and ML using Azure Data Factory, Synapse, and Databricks.
The Azure Data Engineer will work in a cloud-native environment to support Big Data projects by collaborating with analysts and architects to build data solutions. The role requires expertise in Azure, Spark, Databricks, and data processing languages like Python or Scala.
The AWS Data Engineer will design and maintain data platforms, managing data ingestion and transformation for analytics and ML models while implementing CI/CD pipelines and infrastructure migrations on AWS.
AWS Data Engineer based in Italy building data lakes, managing CI/CD pipelines, and maintaining cloud-native monitoring stacks using CloudWatch, Prometheus, and ELK for analytics and ML workloads.
Builds and maintains AWS-based data pipelines, transforming raw data into structured formats for analytics and ML models, with a focus on cloud-native architectures and automation.
The AWS Data Engineer will build and maintain scalable data infrastructure, including data lakes and pipelines, using AWS services, Docker, Kubernetes, and Infrastructure as Code. The role involves collaborating with architects to support analytics and machine learning initiatives.
The Data Architect will design, build, and secure scalable batch and real-time data pipelines on Google Cloud Platform. This senior-level role involves leading data projects to transform raw data into actionable business insights while ensuring data quality and compliance.
AWS Data Engineer designing and building scalable data lakes on AWS, performing data acquisition, transformation, cleansing, and loading for analytics and ML workloads, using Docker, Kubernetes, and serverless Lambda.
The Senior Big Data Engineer will work on large-scale data intelligence projects using Spark, Kafka, and cloud platforms. The role involves data management, analytics, and visualization within an international team.
The AWS Data Engineer will design and implement data pipelines for acquisition, transformation, and loading into cloud-native data lakes to support analytics and machine learning. The role requires expertise in AWS services, big data architectures, and containerization technologies like Docker and Kubernetes.
Senior Data Engineer at Booz Allen Hamilton in Napoli, Italy, designing and implementing scalable data pipelines and platforms across diverse data sources to support fraud detection, cancer research, and national intelligence missions.
Azure Data Engineer bridging Data Science and Engineering in a BI-focused team, building data lake pipelines for analytics and ML using Azure, SQL, Spark/Databricks, and ETL/ELT tools.
The Junior Full-Stack Engineer will design and develop front-end and back-end components using Java, while participating in unit testing and technical documentation. The role involves analyzing functional requirements within an international client-based environment.
Senior full-stack engineer building and scaling PHP/Laravel back-end systems and React front-end components in a pod-driven, AI-assisted development environment.
The Big Data Engineer will design and implement complex data applications using Spark, Kafka, and cloud technologies. The role involves working within multidisciplinary teams to analyze requirements and estimate project timelines.
The Senior Big Data Engineer & Architect will design and implement complex data solutions while collaborating with development teams and international clients. The role requires advanced expertise in Spark, Kafka, NoSQL, and SQL.
Azure Data Engineer bridging Data Science and Data Engineering, building ETL pipelines into data lakes for analytics and ML using Spark, Databricks, and Azure data services in a cloud-native environment.
Azure Data Engineer bridging Data Science and Data Engineering, responsible for data acquisition, transformations, cleansing, and loading into data lakes for analytics and ML workloads in cloud-native Azure environments.
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