Senior Azure Data Engineer (ID:3501)

Stafide; Amsterdam; On-site; EUR 65,000 - 85,000; Full time

Benefits offered by this job

Opportunities for professional growth

Exposure to advanced technologies

Collaborative work environment

Job summary

A leading data engineering firm in Amsterdam is looking for a Senior Azure Data Engineer to design and maintain scalable data architectures. You will be responsible for building reliable ETL workflows, managing data pipelines, and ensuring operational excellence. The ideal candidate has 6-8 years of experience in data engineering with strong skills in Azure Data Factory, Python, and SQL. Join us for continuous learning and growth in a collaborative environment focused on advanced data solutions.

Qualifications

• 6–8 years of overall experience in data engineering and enterprise data platform environments.
• Strong practical experience in building and managing data integration workflows using Azure Data Factory.
• Advanced proficiency in Python for data processing and automation.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Azure Databricks.
• Build and optimize ETL workflows for data ingestion and transformation.
• Monitor data pipelines and resolve incidents within SLAs.

Skills

Azure Data Factory

Python

PySpark

SQL

Apache Airflow

Data Governance

Data Quality

Job description

As a Senior Azure Data Engineer, you will:

• Design, develop, and maintain scalable data pipelines and data processing solutions using Azure Databricks and Azure Data Factory.
• Build, optimize, and support ETL workflows to ensure reliable and timely data ingestion and transformation across enterprise data platforms.
• Manage run and operational activities, including monitoring data pipelines, identifying issues, and resolving incidents within defined SLAs.
• Ensure timely and accurate data onboarding from source systems into enterprise data environments.
• Develop and enhance data processing logic using Python, PySpark, and SQL to support large-scale analytics and reporting needs.
• Implement and manage workflow orchestration and scheduling using Apache Airflow.
• Support data governance and metadata management initiatives using the Atlas Framework.
• Troubleshoot and resolve complex data pipeline, performance, and data quality issues in production environments.
• Collaborate with cross-functional teams to ensure data availability, reliability, and operational stability.
• Create and maintain technical documentation, operational procedures, and best practices for data engineering processes.

What You Bring to the Table:

• 6–8 years of overall experience in data engineering and enterprise data platform environments, with a strong focus on cloud-based data solutions.
• Strong practical experience in building and managing data integration workflows using Azure Data Factory.
• Advanced proficiency in Python for data processing, automation, and pipeline development.
• Solid hands‑on experience with PySpark for large‑scale distributed data processing.
• Strong command of SQL for data querying, transformation, and performance optimization.
• Demonstrated experience in designing and supporting ETL pipelines in production environments.
• Practical experience using Apache Airflow for workflow orchestration and scheduling.
• Working knowledge of the Atlas Framework for data governance and metadata management.
• Experience supporting data platforms in run and operations mode, including incident management and SLA adherence.
• Strong analytical, troubleshooting, and problem‑solving skills.
• Effective communication skills and the ability to collaborate with cross‑functional technical teams.

You Should Possess the Ability to:

• Design and implement scalable, reliable, and high‑performance data engineering solutions on Azure.
• Automate and optimize data processing workflows using Python and PySpark.
• Proactively identify, analyze, and resolve data pipeline and performance issues.
• Manage operational responsibilities while ensuring data accuracy and timely data delivery.
• Work independently while taking ownership of end‑to‑end data engineering tasks.
• Collaborate effectively with technical and non‑technical stakeholders.
• Develop and maintain clear technical documentation and operational runbooks.

What We Bring to the Table:

• Opportunities to work on enterprise‑scale Azure data engineering initiatives.
• Exposure to modern cloud‑based data platforms and advanced data engineering technologies.
• A collaborative and professional environment focused on operational excellence and data reliability.
• Hands‑on experience with complex data ecosystems and enterprise‑level platforms.
• Continuous learning and professional growth opportunities in cloud data engineering.

Let’s Connect

Want to discuss this opportunity in more detail? Feel free to reach out.