Design, build, and maintain robust data pipelines that connect diverse data sources, including databases, APIs, cloud platforms, and third-party systems. You will be responsible for data extraction, transformation, and loading (ETL) processes, ensuring data accuracy, consistency, and reliability Collaborate with cross-functional teams to architect and optimize data storage and retrieval systems. Implement data warehousing solutions that support efficient data querying and analysis while adhering to best practices in data modeling -Familiarity with data integration tools and cloud-based data platforms, such as Kafka, Spark– a must -Proficiency in programming languages like Python for data manipulation and integration tasks - a must -Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field -Proven experience as a Data Engineer, with a strong focus on data integration and ETL processes -Strong understanding of data modeling concepts and database technologies such as SQL, No SQL, and Big Data solutions -Knowledge of data governance, data security, and data privacy principles