The client’s Digital organization is on a transformation journey to modernize data, analytics, and decision support across the bank. A key part of this journey is strengthening Data Warehouse and Data Mart capabilities to ensure that business-critical data for Finance, Risk, and Compliance is well-modeled, reliable, and usable.This assignment focuses on reinforcing and evolving the DW/DM layer, while integrating with upstream data ingestion and lake-based architectures on the AWS data platform.As a Data Engineer with focus on Data Warehousing and Data Modeling, you will play a central role in designing, developing, and maintaining curated data structures supporting analytical, regulatory, and business use cases in a banking context.You will collaborate closely with:Data Engineering LeadsOther Data Engineers (platform, integration, lake-focused)Data Analysts and BI DevelopersTech Leads and Product OwnersFinance, Risk, and Compliance stakeholdersYour work will bridge business context and technical implementation, ensuring data models are scalable, governed, and aligned with platform standards.Key ResponsibilitiesDesign, develop, and maintain Data Warehouse and Data Mart solutions on an AWS-based data platformDevelop and evolve data models supporting financial, risk, and regulatory reportingTranslate business requirements into robust analytical modelsCollaborate with integration teams to ensure reliable upstream dataBuild and maintain transformation pipelines using modern toolingContribute to platform-level architecture and design decisionsApply DevOps principles to ensure reliability and maintainabilityParticipate in solution design, code reviews, and continuous improvementMust-have experience / expertise:Data Warehousing and Data Modeling (DW/DM)Banking domain data, preferably Finance, Risk, or ComplianceStrong SQL and ability to reason about complex data structuresExperience with cloud-based data platforms (AWS or similar)Ability to connect business context with technical implementationExperience in cross-functional, agile teamsExperience with a specific warehouse technology (e.g. Redshift) is valuable but not mandatory Strongly preferred / added value:Data modeling methodologies (dimensional modeling, data marts)Infrastructure as Code (e.g. Terraform)Modern table formats (e.g. Apache Iceberg)Orchestration frameworks (e.g. Apache Airflow)Transformation tools (e.g. dbt)CI/CD pipelines (preferably GitHub Actions)Cloud access management and network infrastructure understandingBanking or financial services experience Ways of working & soft skills:Structured, analytical, and quality-oriented mindsetSelf-driven and proactive, with strong ownershipCollaborative and communicative across technical and business rolesAbility to explain complex data concepts to non-technical stakeholdersExcellent English communication skills (written and spoken) Good to have:Experience with legacy DW technologies such as Oracle RDBMS or InformaticaFamiliarity with SAFe or other agile frameworks