About Position:

We are seeking a highly skilled Azure Cloud Data Engineer with strong expertise in designing, developing, and optimizing enterprise-scale data platforms on Microsoft Azure. The ideal candidate will have hands-on experience in Azure Databricks, Apache Spark, PySpark, Kafka, Python/Scala, and contemporary Data Engineering practices supporting both batch and real-time data processing workloads.

Role: Azure Cloud Data Engineer
Location: Pune, Airoli, Mumbai
Experience: 6 to 8 Years
Job Type: Full Time Employment

What You'll Do:

Design, develop, and maintain scalable data pipelines using Azure Databricks, Apache Spark, and PySpark.
Build robust batch and streaming data ingestion frameworks for enterprise-scale data processing.
Develop ETL/ELT solutions for structured, semi-structured, and unstructured data sources.
Implement data transformation, enrichment, cleansing, and validation processes.
Develop real-time data processing solutions using Kafka and event-driven architectures.




Design and implement streaming pipelines supporting low-latency analytics and business use cases.
Work with large-scale datasets and optimize distributed data processing workloads.
Support real-time monitoring and operational reporting capabilities.
Build and manage cloud-native data solutions on Microsoft Azure.
Develop solutions leveraging Azure Databricks and modern Lakehouse architectures.
Manage and optimize Databricks clusters for performance, scalability, and cost efficiency.
Utilize Delta Lake and cloud storage solutions to support analytics and reporting workloads.
Ensure data quality, integrity, consistency, and reliability across data platforms.
Implement reconciliation, validation, monitoring, and exception handling frameworks.
Troubleshoot pipeline failures and drive root cause resolution.
Support governance, security, and compliance requirements for enterprise data environments.
Collaborate with Architects, Data Scientists, Analysts, Business Stakeholders, and Enginee

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