Qualifications
Requirements:Minimum of 3 years of experience as a Data Engineer. Expertise in SQL and Spark optimization. Experience with data streaming. Proficient in relational and NoSQL databases, and designing Data Warehouses, Data Marts, Data Lakes, and Lakehouse architectures. Distributed processing experience with Hadoop, Spark, and batch/streaming architectures. Development experience in Python, Scala, or Java, applying Clean Code principles. Building pipelines using ETL tools (Azure Data Factory, AWS Glue, SSIS). DataOps/MLOps strategies and CI/CD deployment. Desirable: Certifications in AWS, Azure, or Big Data, and experience with modern architectures such as Data Mesh or Data Fabric.
About the job
Join our dynamic team at Devsu as a Senior Data Engineer in the financial sector, where you will be responsible for the complete lifecycle of data solution development. This includes analysis, design, development, validation, deployment, and maintenance in both OnPremise and Big Data environments. The ideal candidate will possess extensive knowledge in database optimization and will adopt a proactive approach to overcome technical or process-related challenges, ensuring robust and efficient solutions that adhere to industry best practices. We value the ability to lead and collaborate with multidisciplinary teams to expedite goal achievement.
This is a hybrid position based in Quito, Ecuador, where you will be assigned to one of our most important clients in the financial/banking sector of Latin America.
Work in an agile environment with an incredible team dedicated to implementing world-class software products.
About Devsu
At Devsu, we are committed to creating an environment where you can thrive both personally and professionally. Join our team and enjoy stability, growth opportunities, private health insurance, ongoing training programs, and access to AI training resources.
