Operador Sistemas Microsoft Sccm

Decskill; Lisboa; Presencial; EUR 45 000 - 65 000; Tempo integral

Resumo da oferta

Devoteam is seeking a Data Engineer to design and implement scalable data pipelines and processing solutions on Azure and Microsoft Fabric. You will develop ETL/ELT processes for large-scale datasets and work with Lakehouse architectures using Fabric or Azure Databricks.

You will integrate data from multiple sources with Azure Data Factory / Fabric Data Pipelines and build data models in OneLake, ensuring high data quality and platform performance.

Qualificações

• 3+ years experience as a Data Engineer.
• Hands-on experience with Microsoft Azure data services.
• Experience with Microsoft Fabric (Lakehouse, pipelines, notebooks).
• Strong knowledge of PySpark / Spark SQL.
• Experience with Azure Data Factory or Fabric Data Pipelines, Azure Data Lake.

Responsabilidades

• Design and implement scalable data pipelines and data processing solutions using Azure and Microsoft Fabric.
• Develop and optimize ETL/ELT processes for large-scale datasets.
• Work with Lakehouse architectures (Medallion – Bronze, Silver, Gold) using Fabric or Azure Databricks.
• Integrate data from multiple sources using Azure Data Factory / Fabric Data Pipelines.
• Build and maintain data models and Lakehouse structures in OneLake.
• Ensure data quality, reliability, and performance across the platform.
• Optimize Spark workloads and data transformations using PySpark and SQL.
• Collaborate with Data Architects, BI teams and Data Scientists to enable analytics and reporting.
• Contribute to DataOps practices, CI/CD pipelines and automation.
• Support data governance and security best practices across the platform.

Conhecimentos

Data engineering

PySpark

Spark SQL

Azure Data Factory

Azure Databricks

Microsoft Fabric

Azure Data Lake

ETL/ELT development

Ferramentas

Azure Data Factory

Fabric Data Pipelines

Azure Databricks

OneLake

Descrição da oferta de emprego

O TEU PERFIL

Idiomas

At Devoteam, we believe that technology with strong human values can actively drive change for the better. Discover how Tech for People unlocks the future, creating a positive impact on the people and the world around us. We are a global leading player in Digital Transformation for leading organisations across EMEA, with a revenue of €1B. We believe in transforming technology to create value for our clients, partners and employees in a world where technology is developed for people. We are proud of the culture we have built together. We are proud of our people at the service of technology. We are proud of our diverse environment. Because we are #TechforPeople. Join our multidisciplinary team of Cloud experts, Designers, Business consultants, Security experts, Engineers, Developers and other extraordinary talents, spread across more than 20 EMEA countries. Become one of our +10.000 tech and business leaders on cloud, data and cyber security. Let’s fuse creativity with technology together and build innovative solutions that actively change things for the better.

Job Description

• Design and implement scalable data pipelines and data processing solutions using Azure and Microsoft Fabric
• Develop and optimize ETL/ELT processes for large-scale datasets
• Work with Lakehouse architectures (Medallion – Bronze, Silver, Gold) using Fabric or Azure Databricks
• Integrate data from multiple sources using Azure Data Factory / Fabric Data Pipelines
• Build and maintain data models and Lakehouse structures in OneLake
• Ensure data quality, reliability, and performance across the platform
• Optimize Spark workloads and data transformations using PySpark and SQL
• Collaborate with Data Architects, BI teams and Data Scientists to enable analytics and reporting
• Contribute to DataOps practices, CI/CD pipelines and automation
• Support data governance and security best practices across the platform

Qualifications

• Experience as a Data Engineer (3+ years)
• Hands‑on experience with Microsoft Azure data services
• Experience with Microsoft Fabric (Lakehouse, pipelines, notebooks)
• Strong knowledge of PySpark / Spark SQL
• Experience with Azure Data Factory or Fabric Data Pipelines, Azure Data Lake