The Role
Design, develop, maintain, and optimize scalable Azure data engineering solutions. Build and manage Azure Data Factory pipelines, use Azure Databricks for large-scale data processing and transformation, and develop solutions with Python and SQL. Responsibilities include integrating multiple data sources, monitoring and troubleshooting pipeline failures, improving performance and reliability, translating technical requirements, and collaborating with technical and business stakeholders.
Summary Generated by Built In
As an Azure Data Engineer, you will:
- Design, develop, and maintain scalable data engineering solutions on Microsoft Azure.
- Develop and manage data pipelines using Azure Data Factory (ADF).
- Work extensively with Azure Databricks (ADB) for data processing, transformation, and engineering workloads.
- Develop data processing and transformation solutions using Python.
- Write and optimize SQL queries for data extraction, transformation, validation, and analysis.
- Build, monitor, troubleshoot, and optimize Azure-based data pipelines.
- Work with Databricks to process and transform large datasets efficiently.
- Integrate data from multiple sources using Azure data engineering technologies.
- Ensure data pipelines and processing solutions are reliable, scalable, and maintainable.
- Troubleshoot data pipeline failures and performance issues and implement appropriate solutions.
- Collaborate with technical and business stakeholders to understand data requirements and deliver effective data engineering solutions.
What You Bring to the Table:
- 4–6 years of overall professional experience in data engineering or related technology roles.
- Strong hands-on experience as an Azure Data Engineer.
- Strong experience with Azure Data Factory (ADF).
- Hands-on experience with Azure Databricks (ADB).
- Strong programming experience with Python for data engineering and data processing.
- Strong SQL skills.
- Experience developing and maintaining data pipelines using Azure data engineering technologies.
- Experience working with Databricks for data transformation and processing.
- Good understanding of data engineering concepts, data integration, transformation, and pipeline development.
- Ability to troubleshoot and optimize data pipelines and data processing workloads.
You should possess the ability to:
- Design and implement robust and scalable Azure data pipelines.
- Develop efficient data transformations using Python, SQL, and Databricks.
- Build and maintain reliable ADF pipelines.
- Work with Azure Databricks to process and transform data effectively.
- Troubleshoot pipeline failures, data issues, and performance problems.
- Analyze technical requirements and translate them into practical data engineering solutions.
- Optimize data processing workflows for performance, scalability, and reliability.
- Work independently while collaborating effectively with technical and business teams.
- Communicate technical information clearly and contribute effectively to project delivery.
What we bring to the table:
- The opportunity to work on Azure-based data engineering projects.
- Exposure to modern Microsoft Azure data technologies including Azure Data Factory and Azure Databricks.
- Opportunities to work extensively with Python, SQL, and Databricks for data engineering and processing.
- A collaborative environment focused on developing scalable and reliable data solutions.
Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Giftson Paul Davidson
Phone: +31 20 369 0609 ; Extn : 151
LinkedIn: https://www.linkedin.com/in/giftsonpauldavidson/
Skills Required
- 4-6 years of professional experience in data engineering or related technology roles
- Strong hands-on experience as an Azure Data Engineer
- Strong experience with Azure Data Factory
- Hands-on experience with Azure Databricks
- Strong Python programming experience for data engineering and data processing
- Strong SQL skills
- Experience developing and maintaining data pipelines using Azure data engineering technologies
- Experience using Databricks for data transformation and processing
- Understanding of data engineering, data integration, transformation, and pipeline development concepts
- Ability to troubleshoot and optimize data pipelines and data processing workloads
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The Company
What We Do
STAFIDE is a Netherlands-based niche technology talent consulting company operating across Europe. It helps organizations identify, recruit, and deploy technology professionals in areas including cybersecurity, cloud engineering, software development, data analytics, ERP, infrastructure, and digital transformation. Its services include recruitment, workforce engagement, secondment, onboarding support, workforce deployment, and workforce analytics that support technology hiring and expansion.
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