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The Data Engineer will build and maintain scalable real-time data pipelines using Python, SQL, PySpark, Databricks, Kafka, and AWS. The role involves collaborating with data scientists and software engineers to support AI/ML initiatives and manage large-scale sensor data processing.
The Senior Data Engineer will design and deliver data solutions using AWS, Azure, PySpark, and SQL within government and defense sectors. The role involves collaborating with architects and stakeholders to build robust data integration pipelines in a hybrid work environment.
ESPRIMO Srl, società di consulenza informatica che opera dal 2002 su tutto il territorio nazionale ed internazionale, a supporto delle imprese, si colloca nel settore dell’Information Technology proponendosi come…
The Machine Learning Engineer will design, develop, and deploy scalable ML models for Capital Markets applications using Python, PySpark, and various ML frameworks. The role involves managing the full ML lifecycle, including pipeline development, model optimization, and production integration.
Designs and maintains scalable AWS cloud data pipelines, ETL/ELT workflows, and ML integrations using PySpark, AWS Glue, and SageMaker while automating infrastructure with Terraform/Opentofu.
Data Engineer building AWS Glue-based ETL pipelines to ingest data from heterogeneous sources into Amazon S3 and process it across a medallion lakehouse architecture, using PySpark, Python, and SQL.
Lead AWS-based data platform engineering for credit risk models at Commonwealth Bank, focusing on cloud-native architecture, ML workloads via SageMaker, and large-scale data pipelines.
The Lead Data Engineer will build and maintain enterprise data platforms to support analytics, AI, and ML initiatives within a Federal Government environment using Azure Databricks and Microsoft Fabric.
This contract role involves building enterprise data pipelines and Lakehouse architectures for a government organization focused on climate and environmental resources. The position requires expertise in Databricks, PySpark, and Azure cloud services.
The Senior Database & Analytics Engineer will build and govern data foundations within an AI and analytics team, focusing on data modeling, ETL/ELT, and establishing engineering standards. The role involves working with cloud data platforms like Azure and Microsoft Fabric to transform raw data into analytics-ready assets.
The Data Engineer will design and maintain scalable data pipelines and infrastructure for the LANDCROS Connect Insight platform, focusing on big time-series data. The role involves working with cloud-based data warehouses, ETL/ELT processes, and distributed systems to support advanced analytics.
The Lead Data Engineer will design, build, and maintain enterprise-scale data platforms on Microsoft Azure to support advanced analytics. The role involves optimizing ETL/ELT processes, ensuring platform reliability, and collaborating with cross-functional teams using technologies like Azure Data Factory, Databricks, and Synapse Analytics.
Senior Data Engineer designing and building scalable end-to-end data pipelines on AWS using Glue, PySpark, Python, S3, Athena, Redshift, and Airflow.
Data Engineers on 12-month contracts designing enterprise-scale ELT/ETL pipelines and Lakehouse architectures using Databricks, PySpark, and Azure for a government environment and climate-focused organisation.
This role involves migrating Hadoop-based data workloads to AWS and Snowflake within a banking environment. The engineer will build and maintain scalable data pipelines, implement security controls, and optimize cloud data performance.
This Senior Data Engineer role involves leading a migration from AWS to Databricks while maintaining existing AWS workflows. The position requires hands-on expertise in Python, SQL, and cloud-native engineering to design and implement scalable data solutions.
The Senior Data Engineer will design and optimize scalable data pipelines using Azure Databricks, Apache Spark, and Azure Data Factory. The role focuses on building data solutions for the financial sector while ensuring strict adherence to data governance and security standards.
The Senior Data Engineer will design, build, and maintain scalable enterprise data pipelines and cloud-based data platforms using PySpark, Python, SQL, and Azure Data Factory. This role involves integrating complex business systems and partnering with data scientists to operationalize machine learning models and AI initiatives.
This Senior Data Engineer role involves building scalable data pipelines and lakehouse solutions within the Microsoft Azure and Fabric ecosystem to support generative AI and agent-based applications. The position is an initial three-month contract with the potential to transition into a permanent role.
The Lead Data Platform Engineer will architect and manage the enterprise data platform using Microsoft Fabric, Azure, and Power BI. This role involves leading the design of data pipelines, lakehouses, and warehouses while implementing DevOps practices to support the organization's data and AI strategy.
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