Data Engineer

About the RoleWe are looking for a motivated Data Engineer to join our Data Management and AI team and contribute to building scalable data platforms that power analytics and AI initiatives across our digital banking ecosystem.In this role, you will design and develop data pipelines, streaming infrastructure, and data warehouse solutions that enable reliable and high-performance data processing.This is an excellent opportunity for a junior data engineer looking to grow within a fast-paced fintech environment while working on modern data technologies.Team OverviewThe Data Management and AI team works across the entire technology stack within QNBeyond Plus.Our team collaborates with engineering, analytics, and product teams to manage, process, and analyze data that enables innovative digital banking experiences for our customers.Key ResponsibilitiesData Pipeline DevelopmentDesign and build scalable data pipelines for batch and real-time processing.Implement ETL/ELT workflows integrating data from APIs, databases, and event streams.Streaming & Event ProcessingDevelop and maintain streaming data pipelines using tools such as Kafka or similar platforms.Ensure low-latency, reliable, and fault-tolerant data delivery.Data TransformationDevelop data enrichment and transformation workflows to convert raw data into business-ready datasets.Implement SQL transformations across layered architectures (raw → bronze → silver → gold).Data Warehouse DevelopmentDesign and maintain data warehouse models and schemas.Optimize query performance and storage design for analytical workloads.Data Quality & ReliabilityImplement data validation and quality checks.Monitor data pipeline performance and ensure reliability.CollaborationWork closely with engineering, analytics, and product teams to deliver production-ready data solutions.What We Are Looking ForYou must be:Self-motivated, proactive, and results-drivenA team player who enjoys collaboration and learningA problem solver who approaches challenges analyticallyCustomer-oriented, committed to delivering high-quality data solutionsDetail-oriented, especially regarding data quality and complianceAdaptable and eager to grow in a fast-paced fintech environmentRequired QualificationsEducationBachelor’s degree in Computer Science, Computer Engineering, or related fieldTechnical KnowledgeUnderstanding of computer systems and cloud environmentsUnderstanding of network protocols and system connectivitySystems SkillsExperience using Linux command line toolsFamiliarity with SSH, SFTP, Bash, IP, ports, and networking conceptsData Engineering SkillsExperience developing and optimizing ETL/ELT pipelinesExperience with tools such as Informatica PowerCenter, Kafka, NiFi, or similarData & AnalyticsStrong SQL skillsUnderstanding of data warehousing concepts and schema designExperience with data modeling and data lifecycle managementProgrammingProgramming experience using PythonScripting experience using Bash or similar toolsExperience2+ years of experience working with ETL or data engineering workflowsExperience with Informatica PowerCenter and MDMExperience developing and scaling data models within modern data warehouse architecturesExperience implementing data enrichment and transformation logicExperience optimizing queries and storage design for analytics workloadsAt least 1 year of experience in fintech, regulated environments, or PCI/DSS compliance is preferredFamiliarity with performance monitoring tools