Python ETL Pyspark Professional

This role focuses on developing and maintaining robust data pipelines using Python and related technologies. The ideal candidate will be responsible for extracting, transforming, and loading data from various sources, ensuring data quality and integrity, and contributing to the overall data architecture.

Key Responsibilities:

Design, develop, and maintain ETL processes using Python and Pyspark.
Extract data from diverse sources, including databases, APIs, and flat files.
Transform data according to business requirements, ensuring data quality and consistency.
Load data into target systems, such as data warehouses and data lakes.
Monitor and troubleshoot data pipeline performance and resolve issues.
Collaborate with data engineers, data scientists, and business stakeholders.
Implement data validation and quality checks.
Document ETL processes and data flows.

Requirements/Qualifications:

Strong proficiency in Python programming.
Experience with ETL concepts and tools.
Experience with Pyspark for large-scale data processing.
Familiarity with data warehousing and data lake concepts.
Knowledge of SQL and relational databases.
Experience with data quality and data governance principles.
Excellent problem-solving and analytical skills.
Ability to work independently and as part of a team.

About the Company: Infosys Limited is a global leader in providing technology consulting and services. They help businesses navigate their digital transformation journeys by leveraging innovative solutions and expertise across various industries.