About Position:

We are seeking a highly skilled Data Engineer with 5 to 10 years of experience in building enterprise-scale data platforms and modern cloud-based data solutions. The ideal candidate will have solid expertise in Azure, Databricks, SQL, Python, and Generative AI technologies, along with experience developing scalable data pipelines that support Business Intelligence, Advanced Analytics, and AI/ML initiatives.

Role: Data Engineer
Location: All Persistent Locations
Experience: 5-8 yrs
Job Type: Full Time Employment

What You'll Do:

Design, develop, and maintain scalable ETL/ELT pipelines and enterprise data integration frameworks.
Build and optimize data warehouses, data lakes, and cloud-based data platforms.
Develop robust data transformation workflows using Databricks, Python, Spark, and SQL.
Create and manage data models that support reporting, analytics, and AI/ML use cases.
Ensure data quality, integrity, security, availability, and performance across platforms.
Build and maintain scalable data pipelines for structured and unstructured datasets.




Collaborate with analytics, AI/ML, and business teams to deliver trusted, analysis-ready data products.
Support feature engineering and data preparation activities for AI/ML and Generative AI initiatives.
Develop and optimize advanced SQL queries for data extraction, transformation, and validation.
Implement automation, monitoring, alerting, and governance standards across data platforms.
Support cloud data solutions using Azure, Databricks, Snowflake, and related technologies.
Participate in code reviews and promote engineering best practices and development standards.
Work closely with DevOps teams to implement CI/CD practices and deployment automation.
Troubleshoot data pipeline issues and optimize system performance and reliability.
Contribute to Agile ceremonies including sprint planning, estimation, reviews, and retrospectives.
Leverage enterprise-approved AI tools to improve productivity, document

📌 Data Engineer (Pune)
🏢 Persistent Systems
📍 Pune