Azure Data Engineer

Gazelle Global; Amstelveen; Hybrid; EUR 75,000 - 110,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Gazelle Global invites applications for an Azure Data Engineer to join our Amsterdam-based team in the Transaction Banking Data Store. You will design, develop, and operate scalable data solutions in a cloud environment to support data-driven decisions.

As Senior/Lead data professional, you will lead ETL/ELT pipelines, implement CI/CD with Azure DevOps, and collaborate with stakeholders across the organization. Hybrid work with 2 days in the office is offered.

Qualifications

• Strong hands-on experience with Azure Databricks including Unity catalog and DAB.
• Proficiency in Python (OOP), PySpark, and SQL.
• Solid understanding of Apache Spark performance tuning and large-scale data processing.
• Experience building and maintaining ETL/ELT pipelines and modern data integration solutions.
• Experience with Git, CI/CD practices and Azure DevOps.
• Knowledge of data modelling techniques, including dimensional modelling.
• Strong analytical, troubleshooting, and communication skills.
• Experience working in Agile/Scrum and DevOps environments.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data products using Azure Databricks, PySpark, Python, and SQL.
• Build and optimize data ingestion, transformation, and storage solutions for analytics, reporting, and operational use cases.
• Develop and support ETL/ELT processes that integrate data from multiple sources into trusted and governed data platforms.
• Design and review cloud-native solutions leveraging Azure Data Lake Storage (ADLS), Azure Functions, Databricks, and Apache Airflow.
• Ensure data quality, reliability, scalability, monitoring, and operational excellence across the data ecosystem.
• Implement and maintain source control, CI/CD pipelines, and deployment automation using Azure DevOps.
• Collaborate closely with business and technical stakeholders to translate requirements into robust and sustainable solutions.
• Enhance existing data products, optimize platform capabilities, and continuously improve engineering practices.
• Troubleshoot and resolve complex production issues using strong analytical and problem-solving skills.
• Contribute to data architecture, engineering standards, and best practices across the organization.
• Promote innovation, knowledge sharing, and continuous improvement within the Data Engineering Chapter.
• Familiar with Agile, DevOps, and DataOps principles as part of a cross-functional Scrum team.
• Hybrid working with 2 days in office.

Skills

Python

PySpark

SQL

Azure Databricks

Azure Functions

Apache Spark

Unity Catalog

Airflow

ADLS

Git

CI/CD

Azure DevOps

Data modelling

Agile/Scrum

DevOps

Tools

Delta Lake

Iceberg

Job description

As a preferred supplier to one of our biggest Financial Client, I am seeking for Azure Data Engineer for a position in Amsterdam, Netherlands. As a Senior Data Engineer within the Transaction Banking Domain Data Store (TB DDS) team, you will help build and evolve our cloud-based data platform. You will design, develop, and operate scalable data solutions that enable data-driven decision making and support critical Transaction Banking processes.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and data products using Azure Databricks, PySpark, Python, and SQL.
• Build and optimize data ingestion, transformation, and storage solutions for analytics, reporting, and operational use cases.
• Develop and support ETL/ELT processes that integrate data from multiple sources into trusted and governed data platforms.
• Design and review cloud-native solutions leveraging Azure Data Lake Storage (ADLS), Azure Functions, Databricks, and Apache Airflow.
• Ensure data quality, reliability, scalability, monitoring, and operational excellence across the data ecosystem.
• Implement and maintain source control, CI/CD pipelines, and deployment automation using Azure DevOps.
• Collaborate closely with business and technical stakeholders to translate requirements into robust and sustainable solutions.
• Enhance existing data products, optimize platform capabilities, and continuously improve engineering practices.
• Troubleshoot and resolve complex production issues using strong analytical and problem-solving skills.
• Contribute to data architecture, engineering standards, and best practices across the organization.
• Promote innovation, knowledge sharing, and continuous improvement within the Data Engineering Chapter.
• Familiar with Agile, DevOps, and DataOps principles as part of a cross-functional Scrum team.
• Hybrid working with 2 days in office

Requirement

• Strong hands-on experience with Azure Databricks [including Unity catalog, DAB], Apache Airflow, ADLS, and Azure Functions.
• Proficiency in Python (OOP), PySpark, and SQL.
• Solid understanding of Apache Spark performance tuning and large-scale data processing.
• Experience building and maintaining ETL/ELT pipelines and modern data integration solutions.
• Experience with Git, CI/CD practices and Azure DevOps.
• Knowledge of data modelling techniques, including dimensional modelling.
• Strong analytical, troubleshooting, and communication skills.
• Experience working in Agile/Scrum and DevOps environments.

Nice to Have:

• Experience with monitoring, observability, logging, and data lineage.
• Familiarity with Delta Lake, Iceberg, or other modern data lake technologies.
• Knowledge of data governance, metadata management, and data quality frameworks.
• Azure and/or Databricks certifications.
• Experience in Financial Services or Transaction Banking