The Role
Design, build, and maintain scalable Azure data platforms and pipelines using Databricks, PySpark, and structured streaming. Implement data lake/warehouse and serverless architectures, data ingestion, transformation, and cleansing workflows. Monitor DevOps pipelines and production workloads, troubleshoot issues, and drive performance, governance, and operational excellence while collaborating with stakeholders and architects.
Summary Generated by Built In
As a Senior Azure Data Engineer, you will:
- Design, develop, and maintain scalable data platforms and data pipelines on Microsoft Azure.
- Build robust batch and real-time data processing solutions using Azure Databricks, PySpark, and Structured Streaming.
- Develop and optimize data ingestion frameworks for integrating data from multiple structured and unstructured data sources.
- Design and implement modern data lake, data warehouse, and serverless architectures using Azure-native services.
- Collaborate with business stakeholders, architects, and engineering teams to understand data integration, migration, and analytics requirements.
- Develop and maintain data transformation, cleansing, and preprocessing workflows to support enterprise reporting and analytics.
- Monitor and support Azure DevOps pipelines, Databricks workloads, and production data processing environments.
- Implement best practices for data governance, security, performance optimization, and operational excellence.
- Participate in troubleshooting, root cause analysis, and resolution of data platform and pipeline issues.
- Contribute to architecture discussions and recommend scalable, cost-effective cloud-based data solutions.
- Support continuous improvement initiatives related to monitoring, logging, automation, and platform reliability.
What You Bring to the Table:
- 6–8 years of experience in Data Engineering, Data Platform Development, or Cloud Data Solutions.
- Strong hands-on expertise in Python for data engineering and data processing applications.
- Extensive experience with SQL and NoSQL database technologies.
- Proven experience building batch and streaming data pipelines using Azure Databricks and PySpark.
- Strong knowledge of Azure services including Azure Data Lake Storage (ADLS), Azure Databricks, Event Hub, Azure SQL Data Warehouse, Azure Functions, and Serverless Architecture.
- Good understanding of Infrastructure as Code concepts, particularly Terraform.
- Experience designing and implementing enterprise-scale data lake and data warehouse solutions.
- Knowledge of Azure DevOps, CI/CD processes, and cloud deployment methodologies.
- Strong analytical and problem-solving capabilities with the ability to work independently.
- Excellent communication and stakeholder management skills.
You Should Possess the Ability to:
- Design end-to-end data engineering solutions from high-level architectural requirements.
- Build scalable and efficient data ingestion, transformation, and processing pipelines.
- Work with diverse data sources and support enterprise data migration initiatives.
- Optimize data platform performance, reliability, and operational efficiency.
- Collaborate with architects, business users, and development teams to deliver high-quality data solutions.
- Troubleshoot complex data engineering challenges and implement sustainable solutions.
- Adapt quickly to evolving Azure technologies, monitoring tools, and cloud services.
- Ensure data quality, security, governance, and compliance standards are maintained.
What We Bring to the Table:
- Opportunity to work on modern cloud-native data engineering and analytics initiatives.
- Exposure to large-scale Azure data platforms, streaming architectures, and enterprise data ecosystems.
- Collaborative environment with experienced cloud, data, and engineering professionals.
- Challenging projects involving advanced data processing, cloud transformation, and innovation.
- Opportunities for technical leadership, professional development, and continuous learning.
- A culture focused on innovation, knowledge sharing, and engineering excellence.
Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Giftson Paul Davidson
Phone: +31 20 369 0609 ; Extn : 151
LinkedIn: https://www.linkedin.com/in/giftsonpauldavidson/
Skills Required
- 6-8 years of experience in Data Engineering, Data Platform Development, or Cloud Data Solutions.
- Strong hands-on expertise in Python for data engineering and data processing applications.
- Extensive experience with SQL and NoSQL database technologies.
- Proven experience building batch and streaming data pipelines using Azure Databricks and PySpark.
- Experience with Structured Streaming for real-time processing.
- Strong knowledge of Azure services including Azure Data Lake Storage (ADLS), Event Hub, Azure SQL Data Warehouse, Azure Functions, and serverless architectures.
- Good understanding of Infrastructure as Code concepts, particularly Terraform.
- Experience designing and implementing enterprise-scale data lake and data warehouse solutions.
- Knowledge of Azure DevOps, CI/CD processes, and cloud deployment methodologies.
- Strong analytical and problem-solving capabilities and ability to work independently.
- Excellent communication and stakeholder management skills.
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The Company
What We Do
STAFIDE is a Netherlands-based niche technology talent consulting company operating across Europe. It helps organizations identify, recruit, and deploy technology professionals in areas including cybersecurity, cloud engineering, software development, data analytics, ERP, infrastructure, and digital transformation. Its services include recruitment, workforce engagement, secondment, onboarding support, workforce deployment, and workforce analytics that support technology hiring and expansion.
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