Azure Data Engineer

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 (Py

Spark, 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 Dev

Ops

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:

• Py

Spark

• Python

• SQL

• Solid understanding of Apache Spark (core concepts & performance tuning)

• Experience with Big Data technologies

• Exposure to Azure Dev

Ops (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