Senior Azure Data Engineer (ID: 3508)

Stafide

Eindhoven, Netherlands

about 1 month ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

www.jobbird.com

Tech stack

Sql Data Warehouse Microsoft Azure Information Engineering Data Governance DevOps High-Level Architecture Python (Programming Language) SQL Azure NoSQL Standard Sql Azure Data Lake Technical Data Management Systems

+12 more

Data Processing Data Ingestion Azure Data Factory Apache Spark Pyspark Infrastructure Automation Frameworks Deployment Automation Cosmos DB Stream Analytics Data Pipelines Serverless Computing Databricks

Job description

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.

Requirements

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.