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Senior Azure Databricks Engineer(ID: 4002)

Job Description - Senior Azure Databricks Engineer(ID: 4002)

As a Senior Azure Databricks Engineer, you will:
  • Design, develop, and maintain scalable and reliable data processing solutions using Azure Databricks.
  • Build and manage robust batch and streaming data pipelines within Databricks environments.
  • Develop and optimize data transformation and processing solutions using Python, PySpark, and SQL.
  • Design and optimize data models to support scalable processing, performance, and reliability.
  • Manage multiple parallel data processing workflows and shared data sources efficiently.
  • Implement and maintain CI/CD pipelines using Azure DevOps and YAML-based configurations.
  • Apply Infrastructure as Code (IaC) using ARM/Bicep for deployment and infrastructure automation.
  • Monitor, troubleshoot, and optimize data processing workloads and Databricks environments.
  • Collaborate with cross-functional engineering and business teams to deliver reliable and maintainable data solutions.
  • Contribute to Agile development practices and continuously improve engineering standards, system stability, and performance.
What You Bring to the Table:
  • Strong hands-on experience with Azure Databricks as a core data engineering platform.
  • Strong proficiency in Python, PySpark, and SQL.
  • Hands-on experience developing batch and streaming data pipelines.
  • Experience with data modeling, transformation, and optimization within Databricks environments.
  • Good understanding of Azure cloud services relevant to data engineering.
  • Experience with Azure DevOps, CI/CD, and YAML-based pipeline configurations.
  • Hands-on experience with Infrastructure as Code, particularly ARM/Bicep.
  • Experience working in Agile engineering and delivery environments.
  • Understanding of modern cloud-based data architectures and end-to-end data engineering solutions.
  • Strong communication, collaboration, troubleshooting, and problem-solving skills.
You Should Possess the Ability to:
  • Build scalable, high-performance, and reliable data processing solutions using Azure Databricks.
  • Develop efficient PySpark and SQL-based data transformations.
  • Design and manage complex batch and streaming workloads.
  • Optimize data pipelines, processing performance, and resource utilization.
  • Troubleshoot complex data engineering issues and improve system reliability.
  • Implement automated deployment and infrastructure management practices.
  • Make pragmatic technical decisions while maintaining scalability and maintainability.
  • Work effectively with engineering, architecture, and business stakeholders.
  • Drive continuous improvement and maintain high standards of code and solution quality.
What We Bring to the Table:
  • Opportunity to work on enterprise-scale Azure and Databricks data engineering initiatives.
  • Exposure to modern cloud-based data platforms and engineering practices.
  • A collaborative Agile environment focused on technical excellence and innovation.
  • Opportunities to work with advanced data processing, pipeline engineering, and cloud technologies.
  • Continuous learning and opportunities for technical and professional growth.
  • A culture focused on quality, ownership, scalability, and sustainable engineering solutions.

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