Data Engineer

• Design, develop, and maintain scalable ETL pipelines to extract, transform, and load data from multiple sources into enterprise data platforms.
• Implement and manage data integration processes to consolidate data from various systems while ensuring data accuracy, consistency, and reliability.
• Develop and optimize data processing solutions using Python, SQL, and big data technologies such as Hadoop and Spark.
• Monitor, troubleshoot, and enhance ETL workflows to improve performance, data quality, and overall pipeline efficiency.
• Collaborate with cross-functional teams to understand business requirements, support data modelling initiatives, and deliver reliable data solutions.

Requirements

• Proven experience as a Data Engineer with strong expertise in data integration, ETL development, and big data technologies.
• Proficiency in Python and SQL for developing, optimizing, and maintaining data pipelines and data processing solutions.
• Hands-on experience with big data frameworks such as Hadoop, Spark, or similar distributed data processing technologies.
• Solid understanding of data modelling concepts, database design principles, and ETL best practices.
• Strong analytical and problem-solving skills with the ability to ensure data quality, consistency, and scalability across enterprise data platforms.