Analyze, maintain, and enhance existing Python scripts used for data pipelines and automation processes.
Design and implement data transformation workflows, converting unstructured and semi-structured data (e.g., JSON, XML, logs) into structured, analysis-ready formats.
Develop, optimize, and monitor ETL processes to ensure data accuracy, consistency, and reliability across systems.
Collaborate with cross-functional teams to gather data requirements and deliver scalable, efficient data solutions.
Troubleshoot, diagnose, and resolve data pipeline issues to ensure smooth and timely data processing.
Job Qualifications
Strong proficiency in Python, with the ability to read, understand, and modify existing codebases.
Hands-on experience in transforming unstructured or semi-structured data into structured datasets.
Solid knowledge of ETL concepts and tools; experience with Azure Data Factory (ADF) is an advantage.
Advanced SQL skills, including complex queries, joins, data modeling, and performance optimization.
Strong analytical thinking, problem-solving, and troubleshooting skills in data engineering environments.
