Israel A.

-Proficiency in Python, R, and SQL for data manipulation and processing. -Ability to design and implement data models that are scalable, efficient, and meet business requirements. -Expertise in building ETL pipelines to extract data from multiple sources, transform it into a usable format, and load it into data warehouses or data lakes. -Familiar with big data tools and frameworks like Apache Spark, Hadoop, Kafka, etc., for processing large volumes of data. -Experienced in building and maintaining data warehouses, including schema design, optimization, and performance tuning. -Understanding of data quality issues and proficient in implementing data governance processes to ensure data accuracy, consistency, and reliability. -Knowledge of cloud computing platforms like AWS, Azure, and Google Cloud Platform for deploying and managing data infrastructure. -Ability to analyze complex data problems, identify solutions, and implement them effectively. -Strong communication skills to collaborate with cross-functional teams, understand business requirements, and effectively communicate technical solutions. -Willingness to stay updated with the latest trends and technologies in the data engineering field to continuously improve skills and stay competitive.