Senior Azure Data Engineer (ID:3500)

• Design, develop, and maintain scalable ETL/ELT data pipelines using Azure Data Factory (ADF).
• Build and optimize data transformation workflows using Azure Databricks (PySpark) and Python.
• Develop and fine-tune SQL queries, stored procedures, and views for high-volume data platforms.
• Implement data quality frameworks, monitoring, and logging mechanisms across data pipelines.
• Establish and manage CI/CD pipelines for data solutions using Azure DevOps.
• Handle deployment automation for ADF pipelines, Databricks notebooks, and database scripts.
• Manage version control, branching strategies, and environment configuration across development lifecycles.
• Deploy and maintain Azure infrastructure components such as Azure SQL, Event Grid, Virtual Networks (VNet), Private Endpoints (PEP), Key Vaults, and related services using Bicep.
• Ensure adherence to security, governance, and compliance standards across data platforms., * Design and implement high-performance, scalable, and reliable data pipelines.
• Troubleshoot, optimize, and enhance data workflows for performance and cost efficiency.
• Collaborate with cross-functional teams including analytics, application development, and infrastructure teams.
• Automate deployments and enforce best practices for code versioning and release management.
• Translate business and technical requirements into robust data engineering solutions.
• Ensure strong documentation, monitoring, and operational support for data platforms.

What We Bring to the Table:

• Opportunities to work on large-scale, cloud-based data transformation initiatives.
• Exposure to modern Azure data and analytics ecosystem.
• A collaborative environment focused on innovation, automation, and continuous improvement.
• Opportunities to contribute to architecture design and next-generation data platform development.
• A learning-driven culture encouraging adoption of emerging cloud and data engineering technologies.

• 6-8 years of overall experience in Data Engineering or related roles.
• Strong hands-on expertise in Azure Data Factory, Azure Databricks, and PySpark.
• Proficiency in Python programming for data processing and automation.
• Advanced knowledge of SQL performance tuning and data modeling.
• Experience implementing DevOps practices in data engineering environments using Azure DevOps.
• Solid understanding of Azure cloud infrastructure and Infrastructure as Code using Bicep.
• Experience working with enterprise-scale data ingestion, transformation, and orchestration.
• Familiarity with data governance, security best practices, and compliance frameworks.