Senior azure data engineer (id: 3508)
Stafide
Eindhoven, Netherlands
1 day ago
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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
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.
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