DE&A - Core - Cloud Data Engineering - Azure Data Engineer

Zensar Technologies Limited is seeking a highly skilled Senior Data Engineer with deep expertise in Databricks, Azure, Delta Lake, and Spark. In this role you will architect end-to-end data solutions, develop robust data pipelines, and enable data-driven decision-making across the organization while adhering to modern data engineering best practices.

• 5+ years of hands-on experience in data engineering, with at least 3 years focused on Databricks and Azure.
• Strong proficiency in Spark (PySpark/Scala) and Delta Lake for large-scale data processing.
• Deep understanding of Azure services such as Azure Data Lake Storage, Azure Synapse, Azure Functions, and Azure DevOps.
• Experience designing and implementing ETL/ELT pipelines using modern orchestration tools.
• Proficiency in SQL and programming languages like Python or Scala.
• Knowledge of data modeling, data warehousing concepts, and best practices for data governance.
• Demonstrated ability to optimize performance and cost in cloud environments.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative team.
• Strong communication skills to convey technical concepts to non-technical stakeholders.
• Bachelor s or Master s degree in Computer Science, Engineering, or a related field.

• Design and implement scalable data architectures on Azure using Databricks, Delta Lake, and Spark.
• Develop, test, and maintain ETL/ELT pipelines that ingest and transform large volumes of data.
• Collaborate with data scientists, analysts, and business stakeholders to translate requirements into technical solutions.
• Optimize performance and cost of data workloads through tuning, caching, and resource management.
• Implement data governance, security, and compliance controls in line with enterprise standards.
• Automate deployment and monitoring of data pipelines using CI/CD tools and Azure DevOps.
• Create and maintain comprehensive documentation for data models, pipelines, and processes.
• Mentor junior engineers and promote best practices in data engineering and cloud services.
• Evaluate emerging technologies and recommend enhancements to the data platform.
• Troubleshoot and resolve production issues, ensuring high availability and reliability.