Data Engineer – Data Platforms (Azure)

Job Title: Data Engineer – Data Platforms (Azure)

Experience: 6–9 Years

Location: Bangalore (BLR)

Role Overview

We are seeking an experienced Data Engineer with strong expertise in Microsoft Azure Data Platform technologies. The ideal candidate will design, build, and optimize scalable data pipelines and modern data solutions to support business intelligence, analytics, and data-driven decision-making.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Azure data services.
• Build and manage data ingestion, transformation, and integration workflows from multiple data sources.
• Develop and optimize data models, data lakes, and data warehouses for analytics and reporting.
• Work with cross-functional teams to understand business requirements and deliver robust data solutions.
• Ensure data quality, integrity, security, and governance across enterprise data platforms.
• Monitor, troubleshoot, and optimize data pipeline performance and reliability.
• Implement CI/CD practices and automation for data engineering workflows.
• Collaborate with architects, analysts, and developers to support enterprise data initiatives.

Required Skills

• Strong experience with Azure Data Factory (ADF), Azure Synapse Analytics, Azure Data Lake Storage (ADLS), and Azure SQL Database.
• Hands-on experience with PySpark, Azure Databricks, and Apache Spark.
• Proficiency in SQL and Python for data processing and transformation.
• Experience with ETL/ELT design, data modeling, and performance tuning.
• Knowledge of Azure DevOps, Git, and CI/CD pipelines.
• Understanding of data governance, security, and best practices.
• Familiarity with Power BI or other reporting tools is an added advantage.

Preferred Qualifications

• Experience working on enterprise-scale cloud data platforms.
• Microsoft Azure Data Engineer certifications are preferred.
• Strong analytical, troubleshooting, and communication skills.
• Ability to work independently and collaborate effectively within cross-functional teams.