About Position:

We are seeking an experienced Azure Data Engineer with robust expertise in Azure Databricks, Spark, Python, PySpark, and SQL. The ideal candidate will be responsible for designing, developing, and maintaining scalable cloud-based data platforms and enterprise data pipelines. You will play a key role in enabling analytics, reporting, business intelligence, and machine learning initiatives through high-performance and reliable data engineering solutions.

• Role: Azure Data Engineer - Databricks & PySpark
• Location: All Persistent Locations
• Experience: 5 to 11 Years
• Job Type: Full-Time Employment

What You'll Do:

• Design, develop, and maintain enterprise-scale data pipelines using Azure cloud services.
• Build scalable ETL/ELT frameworks for processing structured, semi-structured, and unstructured datasets.
• Develop high-performance Spark applications using PySpark and Databricks.
• Create and manage data ingestion, transformation, validation, and orchestration processes.




• Design and implement modern data lake and Lakehouse architectures using Azure technologies.
• Optimize data processing workloads for scalability, reliability, performance, and cost efficiency.
• Develop reusable data engineering frameworks and automation capabilities.
• Support analytics, business intelligence, reporting, and machine learning initiatives through robust data solutions.
• Ensure data quality, governance, monitoring, security, and compliance standards are implemented across data platforms.
• Collaborate with business users, architects, analysts, and cross-functional engineering teams to deliver data-driven solutions.
• Perform production support, troubleshooting, root cause analysis, and performance tuning of data pipelines.
• Participate in code reviews, CI/CD implementation, deployment automation, and DevOps practices.
• Contribute to data platform modernization and continuous improvement initiatives.

Expertise You'll Bring:

• 5-11 years of experience in D

📌 Azure Data Engineer (Pune)
🏢 Persistent Systems
📍 Pune