Data Engineer - Python/PySpark

Overview As a Data Engineer, you will design and maintain scalable data pipelines to support large-scale data processing. You will work within cross-functional agile teams to deliver KYC/AML data solutions that enable client onboarding and lifecycle management. Your work will focus on optimizing Spark-based ETL/ELT jobs and integrating structured and unstructured data from varied sources. This role offers the opportunity to impact data reliability and performance in a cloud-enabled big data environment. Join us to help shape data-driven workflows in a fast-paced software context. ResponsibilitiesDesign, develop, and maintain scalable data pipelinesProcess large volumes of structured and unstructured dataImplement KYC/AML data solutions supporting client lifecycle managementOptimize Spark jobs for performance and reliabilityCollaborate with cross-functional agile teams and stakeholders Key requirements3–6 years of experience as a Data EngineerStrong Python and PySpark expertiseExperience building scalable ETL/ELT pipelines in big data environmentsHands-on experience with Spark, Hadoop, Kafka, and cloud platformsSolid knowledge of SQL and NoSQL databasesUnderstanding of KYC/AML and Client Onboarding domainscross-functional collaborationagile mindsetproblem solvingPythonPySparkSpark