Python Programming : Strong ability to write clean and efficient code.
Spark SQL : Good understanding of Spark SQL for distributed data processing.
Data Processing : Experience with large datasets and structured data manipulation.
SQL Fundamentals : Ability to write queries and optimize database performance.
Problem-Solving : Analytical mindset to debug and optimize workflows.
Preferred Skills :
AWS Cloud Services : Familiarity with S3, Redshift, Lambda, EMR is an advantage.
ETL Development : Understanding of ETL processes and data engineering principles.
Version Control : Experience using Git for collaborative development.
Big Data Tools : Exposure to Hive, PySpark , or similar technologies.
Roles & Responsibilities
Develop and optimize Python scripts for data processing and automation.
Write efficient Spark SQL queries for handling large-scale structured data.
Assist in ETL pipeline development and maintenance.
Support data validation and integrity checks across systems.
Collaborate with teams to implement cloud-based solutions (AWS preferred).
Optimize performance of data queries and workflows.
Troubleshoot and debug issues in existing applications.
Document processes and ensure best practices in coding and data handling.
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Data Engineer • erode, tamil nadu, in
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