Data Pipeline Development & Operations
- Design, build, and operate scalable and reliable data pipelines on the Databricks platform
- Develop end-to-end data workflows from ingestion through transformation to consumption
- Implement robust error handling, monitoring, and alerting mechanisms
- Ensure data pipeline reliability, performance, and maintainability
- Optimize pipeline performance through productive Spark job design and cluster configuration
- Manage and orchestrate complex data workflows using Databricks Jobs and workflows

Legacy Code Modernization
- Refactor legacy code and data pipelines to PySpark for improved performance and scalability
- Migrate traditional ETL processes to modern ELT patterns on Databricks
- Assess existing codebases and identify opportunities for optimization and modernization
- Ensure backward compatibility and data integrity during migration processes
- Document refactoring approaches and create migration playbooks
- Collaborate with stakeholders to minimize disruption during code transitions

Data Engineering Excellence




- Implement data quality checks and validation frameworks
- Design and maintain Delta Lake tables with appropriate optimization strategies
- Develop reusable code libraries and frameworks for common data engineering tasks
- Follow software engineering best practices including version control, testing, and CI/CD
- Participate in code reviews and provide constructive feedback to team members
- Troubleshoot and resolve data pipeline issues in production environments

Collaboration & Knowledge Sharing
- Work closely with data architects, analysts, and business stakeholders
- Collaborate with Infrastructure (Infra), Applications (Apps), and Cyber teams
- Share knowledge and best practices with Team *****
- Mentor junior data engineers on PySpark and Databricks technologies
- Document technical solutions and maintain comprehensive documentation

Essential Technical Skills
- Data Engineering: Strong foundation in da

📌 Senior Data Engineer (Pune Division)
🏢 ANRGI TECH
📍 Pune Division