Azure Data Engineer

STAFIDE; Amsterdam; On-site; EUR 90,000 - 130,000; Full time

Job summary

STAFIDE is looking for a senior Data Engineer to design, develop, and maintain robust data pipelines using Databricks, PySpark, Azure Data Factory, and Python.

You will focus on data governance, data quality, and data lineage while delivering scalable, enterprise-grade data solutions across cloud technologies.

Qualifications

• 10+ years of experience in Data Engineering.
• Strong hands-on experience with Databricks.
• Strong experience with PySpark.
• Experience with Azure Data Factory (ADF).
• Strong Python scripting skills.
• Experience implementing data governance, data quality, and data lineage.
• Proven experience designing and maintaining robust data pipelines.

Responsibilities

• Build scalable and reliable data pipelines.
• Develop and optimize data processing workflows.
• Apply data governance and data quality principles across data solutions.
• Work effectively with Databricks and Azure Data Factory.
• Troubleshoot and optimize data pipelines and processing workflows.

Skills

Data pipeline design

Cloud data engineering

Problem solving

Tools

Databricks

PySpark

Azure Data Factory

Python

Job description

• Design, develop, and maintain robust data pipelines using Databricks, PySpark, Azure Data Factory, and Python.
  
• Implement scalable data solutions with a strong focus on data governance, data quality, and data lineage.
• Develop and optimize data processing workflows to support reliable and high-quality data delivery.
• Work with cloud-based data engineering technologies to build and maintain enterprise-grade data solutions.

What You Bring to the Table

• 10+ years of experience in Data Engineering.
  
• Strong hands-on experience with Databricks.
• Strong experience with PySpark.
• Experience with Azure Data Factory (ADF).
• Strong Python scripting skills.
• Experience implementing data governance, data quality, and data lineage.
• Proven experience designing and maintaining robust data pipelines.

You should possess the ability to

• Build scalable and reliable data pipelines.
  
• Apply data governance and data quality principles across data solutions.
• Develop efficient data processing solutions using PySpark and Python.
• Work effectively with Databricks and Azure Data Factory.
• Troubleshoot and optimize data pipelines and processing workflows.

What We Bring to the Table

• Opportunity to work on large-scale data engineering solutions.
  
• Exposure to modern data technologies including Databricks, PySpark, Azure Data Factory, and Python.
• Opportunity to contribute to data governance, data quality, and data lineage initiatives.
• A professional environment focused on building robust and scalable data solutions.