The Role
Designs, develops, and maintains scalable Azure and on-premises data pipelines, enterprise data products, ETL/ELT processes, and data warehouses. Uses Azure Data Factory, Synapse, ADLS, Databricks, SQL Server, SSIS, SQL, and Python. Builds CI/CD pipelines with Azure DevOps and GitHub, optimizes performance and data quality, troubleshoots production issues, documents solutions, and collaborates with stakeholders in Agile teams.
Summary Generated by Built In
As a Senior Data Engineer – Azure, you will:
- Design, develop, and maintain scalable and reliable data pipelines and enterprise data products.
- Build and support data engineering solutions across cloud and on-premises environments.
- Develop solutions using Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure Databricks, SQL Server, and SSIS.
- Design and implement robust ETL/ELT processes for enterprise data solutions.
- Develop and maintain CI/CD pipelines using Azure DevOps and GitHub.
- Apply Git-based development practices including branching, pull requests, code reviews, and release management.
- Optimize data pipelines, ETL/ELT processes, and data models for performance, stability, scalability, and data quality.
- Troubleshoot and resolve production data engineering and pipeline issues.
- Collaborate with business and technical stakeholders to understand requirements and deliver effective data solutions.
- Maintain clear and accurate technical documentation for data solutions and processes.
- Contribute to the delivery and continuous improvement of production-ready data solutions within an Agile environment.
What You Bring to the Table:
- 6+ years of overall professional experience in Data Engineering, Data Warehousing, or a related field.
- Strong hands-on experience with Azure Data Factory (ADF).
- Strong experience with Azure Synapse Analytics.
- Strong experience with Azure Data Lake Storage (ADLS).
- Strong hands-on experience with Azure Databricks.
- Strong experience with SQL Server, T-SQL, and SQL Server Integration Services (SSIS).
- Hands-on experience with CI/CD, Azure DevOps, and GitHub.
- Strong proficiency in SQL and Python.
- Good knowledge of data warehousing, dimensional modelling, and ETL/ELT concepts.
- Experience delivering production-ready data solutions in an Agile environment.
- Strong knowledge of Git-based development practices, including branching, pull requests, code reviews, and release management.
- Strong analytical and troubleshooting skills.
- Strong communication and stakeholder-management skills.
You should possess the ability to:
- Design and develop scalable, reliable, and maintainable data pipelines.
- Build enterprise data solutions using the Azure data engineering ecosystem.
- Develop and optimize ETL/ELT workflows using Azure Data Factory, Databricks, and SSIS.
- Work effectively with Azure Synapse, ADLS, SQL Server, and T-SQL.
- Develop efficient and high-quality SQL and Python solutions.
- Design and work with data warehouses and dimensional data models.
- Optimize data pipelines and data models for performance, stability, scalability, and data quality.
- Build and manage CI/CD pipelines using Azure DevOps and GitHub.
- Follow Git-based development practices and participate effectively in code reviews and release management.
- Troubleshoot complex production issues and identify appropriate root causes and solutions.
- Work effectively across cloud and on-premises data environments.
- Collaborate with business and technical stakeholders and translate requirements into technical solutions.
- Document technical solutions, processes, and implementation details clearly.
- Work effectively within Agile teams and take ownership of assigned deliverables.
What we bring to the table:
- The opportunity to work on scalable and enterprise-grade Azure data engineering solutions.
- Exposure to a broad Azure data technology stack including ADF, Synapse, ADLS, and Databricks.
- Opportunities to work extensively with SQL Server, T-SQL, SSIS, SQL, and Python.
- Hands-on experience with modern CI/CD, Azure DevOps, GitHub, and Git-based development practices.
- Opportunities to work across both cloud and on-premises data environments.
- Exposure to enterprise data warehousing, dimensional modelling, ETL/ELT, and data product development.
- A collaborative Agile environment involving business and technical stakeholders.
- Opportunities to contribute to performance optimization, data quality, production support, and continuous improvement.
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+ years of professional experience in Data Engineering, Data Warehousing, or a related field
- Strong hands-on experience with Azure Data Factory
- Strong experience with Azure Synapse Analytics
- Strong experience with Azure Data Lake Storage
- Strong hands-on experience with Azure Databricks
- Strong experience with SQL Server, T-SQL, and SSIS
- Hands-on experience with CI/CD, Azure DevOps, and GitHub
- Strong proficiency in SQL and Python
- Knowledge of data warehousing, dimensional modeling, and ETL/ELT concepts
- Experience delivering production-ready data solutions in an Agile environment
- Knowledge of Git-based development practices, including branching, pull requests, code reviews, and release management
- Strong analytical and troubleshooting skills
- Strong 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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