ETL Development
Design, develop, and maintain ETL pipelines using Python and PySpark
Extract, transform, and load data from multiple structured and unstructured sources
Build reusable and scalable data processing frameworks
Ensure data quality, validation, and consistency
PySpark / Big Data Processing
Develop and optimize PySpark jobs for large-scale data processing
Work with Spark DataFrames and RDDs
Implement transformations, aggregations, and joins in Spark
Optimize jobs for performance and scalability
Python Development
Develop backend logic and data processing scripts using Python
Write modular, reusable, and efficient code
Integrate APIs and automate workflows
Data Management & Integration
Work with data lakes and warehouses (S3, HDFS, Redshift, Hive)
Handle file formats like Parquet, ORC, JSON, CSV
Perform data cleansing, enrichment, and transformation
Collaboration & Support
Work with data engineers, analysts, and business stakeholders
Debug and troubleshoot ETL/data pipeline issues
Participate in Agile/Scrum ceremonies
Maintain documentation and coding standards

Core Skills
2-5 years of experience in Python and ETL development
Hands-on experience with PySpark (mandatory)
Strong understanding of data processing and pipelines
Solid knowledge of SQL and database concepts
Technical Skills
Experience with Apache Spark ecosystem
Good knowledge of data structures and algorithms (basic to intermediate)
Familiarity with Big Data technologies (Hadoop, Hive)
Experience with version control (Git)
Understanding of REST APIs and integrations

* Primary skills:Domain->Finacle-Core-Functional->Finacle-Core-WMS->Grand Master,Technology->ETL & Data Quality->ETL - Others,Technology->Machine Learning->Python