Senior Azure Data Engineer (ID: 3508)

Stafide

Eindhoven

On-site

EUR 80,000 - 100,000

Full time

14 days+

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Job summary

A leading data solutions firm located in Eindhoven is seeking a Senior Azure Data Engineer to design and implement scalable data solutions. This role emphasizes independent solution design and collaboration with cross-functional teams. Candidates should have 8-10 years of experience in data engineering within the Azure ecosystem, strong skills in Python and Scala, and hands-on experience with a range of Azure services including Databricks and Data Lake Storage. The position offers involvement in transformative cloud projects and an ownership-driven culture.

Qualifications

  • 8-10 years of hands-on experience in data engineering and Azure ecosystem.
  • Strong expertise in Python and Scala for data processing.
  • Deep knowledge of SQL and NoSQL databases.
  • Advanced experience with PySpark and Spark-SQL.
  • Strong hands-on experience with Azure Databricks.
  • Practical experience with Azure Data Lake Storage (ADLS) and Azure Data Factory (ADF).
  • Experience working with Stream Analytics, SQL Data Warehouse, and Cosmos DB.
  • Solid exposure to Azure DevOps practices.

Responsibilities

  • Design and implement scalable data solutions based on high-level architecture.
  • Build and optimize end-to-end data pipelines using Azure Databricks.
  • Load and process data from disparate data sources into centralized platforms.
  • Perform preprocessing, transformation, and enrichment using PySpark and Spark-SQL.
  • Work directly with stakeholders to gather business requirements for data pipeline and lake migration initiatives.
  • Develop and maintain data solutions using Azure services.
  • Implement serverless architectures using Azure Functions.
  • Monitor and manage Azure DevOps and Databricks pipelines.
  • Participate in production support and incident resolution.
  • Contribute to data governance practices using Unity Catalog.
  • Support ARM template-based infrastructure deployments.
  • Continuously improve pipeline performance, reliability, and scalability.

Skills

Data engineering experience
Azure ecosystem expertise
Python
Scala
SQL and NoSQL databases
PySpark
Spark-SQL
Azure Databricks
Azure Data Lake Storage (ADLS)
Azure Data Factory (ADF)
Azure DevOps practices
Data governance

Job description

As a Senior Azure Data Engineer, you will:
  • Design and implement scalable data solutions based on high-level architecture.
  • Build and optimize end-to-end data pipelines using Azure Databricks.
  • Load and process data from disparate data sources into centralized platforms.
  • Perform preprocessing, transformation, and enrichment using PySpark and Spark-SQL.
  • Work directly with stakeholders to gather business requirements for data pipeline and lake migration initiatives.
  • Develop and maintain data solutions using Azure services such as ADLS, ADF, Cosmos DB, and Azure SQL DW.
  • Implement serverless architectures using Azure Functions.
  • Monitor and manage Azure DevOps and Databricks pipelines.
  • Participate in production support and incident resolution.
  • Contribute to data governance practices using Unity Catalog.
  • Support ARM template-based infrastructure deployments.
  • Continuously improve pipeline performance, reliability, and scalability.
What You Bring to the Table:
  • 8-10 years of hands‑on experience in data engineering and Azure ecosystem.
  • Strong expertise in Python and Scala for data processing.
  • Deep knowledge of SQL and NoSQL databases.
  • Advanced experience with PySpark and Spark-SQL.
  • Strong hands‑on experience with Azure Databricks.
  • Practical experience with Azure Data Lake Storage (ADLS) and Azure Data Factory (ADF).
  • Experience working with Stream Analytics, SQL Data Warehouse, and Cosmos DB.
  • Solid exposure to Azure DevOps practices.
You should possess the ability to:
  • Design independent solutions from high‑level architecture without constant supervision.
  • Translate business requirements into technical data solutions.
  • Handle complex data ingestion from multiple heterogeneous sources.
  • Optimize Spark workloads for performance and cost efficiency.
  • Monitor and troubleshoot production pipelines effectively.
  • Collaborate cross‑functionally with business and technical stakeholders.
  • Implement data governance and access control using Unity Catalog.
  • Automate deployments using DevOps and Infrastructure-as-Code practices.
What We Bring to the Table:
  • Opportunity to work on large‑scale Azure data transformation projects.
  • Exposure to modern cloud‑native and serverless architecture.
  • Collaborative environment with cross‑functional stakeholders.
  • Ownership‑driven culture where independent solution design is valued.
  • Hands‑on experience with enterprise‑grade data platforms.
  • Involvement in cloud migration and lakehouse implementations.
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