Azure Databricks Engineer (ID:

As an Azure Databricks Engineer, you will:

• Design, develop, and maintain robust and reliable data processing solutions using Azure Databricks, Python, and PySpark.
  
• Build and manage both batch and streaming data processing workflows within Databricks.
  
• Design appropriate data models and processing architectures within the Databricks environment.
  
• Manage multiple parallel data processes working on shared source data.
  
• Develop scalable and maintainable data solutions while ensuring high standards of quality, reliability, and performance.
  
• Implement and maintain CI/CD pipelines using Azure and YAML.
  
• Work with Infrastructure as Code (IaC) using ARM/Bicep.
  
• Continuously improve existing solutions, reduce technical debt, and make pragmatic technical decisions.
  
• Collaborate effectively within an Agile engineering environment.
  

What You Bring to the Table:

• 8+ years of overall professional experience in data engineering/software engineering.
  
• Strong hands-on experience with Azure Databricks as a core technology.
  
• Deep expertise in Python, PySpark, and SQL.
  
• Proven experience designing and managing data processing solutions within Databricks.
  
• Strong experience handling both streaming and batch data.
  
• Experience designing data models specifically for Databricks-based processing environments.
  
• Solid experience with Microsoft Azure cloud services.
  
• Hands-on experience with CI/CD pipelines using YAML.
  
• Experience with Infrastructure as Code, particularly ARM/Bicep.
  
• Experience working in an Agile environment.
  

You should possess the ability to:

• Build stable, scalable, reliable, and maintainable Databricks solutions.
  
• Apply strong problem-solving and analytical skills to complex data-processing challenges.
  
• Make well-founded technical decisions in complex and evolving architectures.
  
• Work effectively with large-scale batch and streaming data processes.
  
• Manage and coordinate multiple parallel data-processing workloads.
  
• Identify and address technical debt proactively.
  
• Continuously improve data-processing solutions and engineering practices.
  
• Collaborate and communicate effectively with technical and cross-functional teams.
  
• Follow a structured and pragmatic engineering approach without unnecessary over-engineering.
  
• Balance engineering best practices with practical business and technical requirements.
  

What We Bring to the Table:

• An opportunity to work on complex Azure Databricks and data-processing solutions.
  
• Exposure to modern cloud, data engineering, CI/CD, and Infrastructure as Code practices.
  
• A collaborative Agile engineering environment focused on quality and continuous improvement.
  
• Opportunities to work with both batch and streaming data-processing architectures.
  
• A technically challenging environment where pragmatic, scalable, and maintainable solutions are valued
  

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
E-mail: giftson.p@stafide.nl
LinkedIn: https://www.linkedin.com/in/giftsonpauldavidson/