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.

Data Engineer