• Identify data quality issues and implement solutions to improve data accuracy, consistency, and reliability
• Design and build features from raw data to support machine learning and analytics use cases
• Build and maintain robust data pipelines for efficient data processing and flow
• Integrate data from multiple sources and systems to create unified, usable datasets

Requirements

• 4+ years of relevant experience in data engineering and ETL, or related roles
• Strong hands-on experience in data quality improvement initiatives
• Proven expertise in feature engineering for analytics or ML use cases
• Solid experience in data pipeline development using modern data tools
• Experience with data integration services across varied data sources and systems