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Senior Data Engineer Azure (ID: 4054)

Tech Jobs Netherlands - STAFIDE
Warsaw, Poland
Full-time

About this role

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.

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