Job Description

Job Title: Senior Azure Data Engineer / Azure Data Engineer

Location: PAN India

Experience: 5+ Years

Notice Period: Immediate / Up to 15 Days


Role Overview

We are looking for a Senior Azure Data Engineer with strong hands-on experience in Azure data services, data ingestion, and big data processing. The ideal candidate should have solid coding skills (PySpark, Python, SQL) , deep understanding of Spark core , and strong communication abilities to work with cross-functional teams.


Key Responsibilities

  • Design, build, and maintain scalable data storage solutions using Azure SQL Database, Azure Data Lake, and Azure Blob Storage
  • Develop and manage robust data pipelines for ingestion, processing, and transformation
  • Create optimized data models to support analytics and reporting needs
  • Build and maintain ETL/ELT pipelines using Azure Data Factory or similar tools
  • Process and transform large-scale datasets using Azure Databricks and Apache Spark
  • Implement data validation, cleansing, and quality checks to ensure data accuracy and reliability
  • Ensure data security, governance, and compliance across the data platform
  • Collaborate with data engineers, architects, and business stakeholders to translate requirements into scalable Azure data architectures
  • Support CI/CD processes using Azure DevOps


Required Skills & Qualifications

  • 5+ years of experience as a Data Engineer , with strong focus on Azure
  • Hands-on expertise in:
  • Azure Data Factory
  • Azure Databricks
  • Azure Data Lake & Blob Storage
  • Strong coding skills in:
  • PySpark
  • Python
  • SQL
  • Solid understanding of Apache Spark (core concepts & performance tuning)
  • Experience with Big Data technologies
  • Exposure to Azure DevOps (CI/CD, pipelines)
  • Strong analytical and problem-solving skills
  • Good communication skills and ability to work with cross-functional teams


Nice to Have

  • Experience with data governance and security frameworks
  • Performance optimization for Spark and Databricks workloads
  • Experience working in large-scale, enterprise data platforms

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