Senior Data Engineer/ Data Architect (Retail Banking Digital Transformation)
Mô tả công việc
- Develop and maintain Enterprise Data Architecture, Data Architecture Principles, standards, and blueprints aligned with business strategy and technology direction. - Analyze business capabilities, data requirements, and existing systems to design target-state data architectures and transition roadmaps. - Design end-to-end data flows and data integration architectures across source systems, Data Warehouse, Data Lake / Lakehouse, Data Mart, BI, and downstream applications. - Design conceptual, logical, and physical data models to ensure consistency, scalability, performance, reusability, and alignment with enterprise data standards. - Define and govern data architecture patterns for data ingestion, integration, transformation, storage, serving, and consumption, including Batch, Near Real-time, and Streaming architectures. - Design and review Data Warehouse, Data Lake / Lakehouse, Data Vault, and Data Mart architectures based on business and technical requirements. - Define standards and guidelines for data modeling, naming conventions, data structures, metadata, data lineage, data quality, and data lifecycle management. - Review and approve data architecture and data model designs proposed by project teams, vendors, and implementation partners. - Collaborate with Data Governance, Data Engineering, BI, Application Architecture, Infrastructure, Security, and business teams to ensure data solutions are aligned with enterprise architecture and governance requirements. - Identify architectural risks, technical debt, data duplication, and inconsistencies across systems, and propose appropriate remediation and modernization approaches. - Evaluate new data technologies, platforms, and architectural patterns and provide recommendations based on business value, scalability, performance, security, and total cost of ownership. - Support project teams during implementation to ensure delivered solutions comply with approved architecture and design. - Build and maintain architecture artifacts, including Data Architecture Blueprints, Data Flow Diagrams, Conceptual and Logical Data Models, architecture principles, standards, decision records, and roadmaps. - Perform other tasks as assigned by management.
Yêu cầu ứng viên
- Bachelor’s degree in Computer Science, Data Science, Information Systems, Software Engineering, or equivalent practical experience. - Strong background in Data Architecture, Data Engineering, Data Warehouse, or enterprise-scale data platforms. - Strong understanding of Data Architecture principles, Enterprise Data Architecture, Data Integration Architecture, and modern data platform architectures. - Strong knowledge of Data Warehouse, Data Lake, Lakehouse, Data Mart, Operational Data Store, and database design principles. - Strong hands-on experience in data modeling, including Conceptual Data Model, Logical Data Model, and Physical Data Model. - Solid understanding of dimensional modeling, normalized data models (3NF), and enterprise data modeling techniques. - Hands-on experience with Databricks (Cloud-based) or Oracle Data Warehouse environments for designing enterprise data solutions (mandatory requirement). - Experience in relational databases and data platforms, including Oracle, SQL Server, MySQL, and DB2 (DB2 is highly preferred). - Strong understanding of data integration patterns, including Batch, CDC, API-based integration, Event-driven, Near Real-time, and Streaming. - Experience in designing end-to-end data flows from source systems through ingestion, storage, transformation, and consumption layers. - Experience with Cloud platforms (AWS / Azure / GCP) and cloud-based data architectures. - Ability to translate business requirements and business capabilities into scalable data architecture and data models. - Ability to review technical designs, identify architectural risks and trade-offs, and provide clear recommendations. - Strong analytical thinking, structured problem-solving, and ability to work with complex enterprise environments. - Strong communication and stakeholder management skills, with the ability to collaborate across business, architecture, engineering, infrastructure, and vendor teams. - Experience with Agile Software Development and a solid understanding of Agile principles, Scrum methodology, and collaborative delivery models. - Team player with a proactive attitude and willingness to continuously learn and self-develop.
- Nice to Have (Strong Plus): - Experience or knowledge of IBM Banking Data Model or other enterprise banking data models. - Experience with Data Vault 2.0, including Raw Vault, Business Vault, PIT, and Bridge structures. - Experience with Databricks Lakehouse Architecture, Unity Catalog, and Medallion Architecture. - Understanding of banking data domains such as Customer, Account, Product, Transaction, Finance, Risk, and Regulatory Reporting. - Experience with Data Governance concepts and tools, including Business Glossary, Metadata Management, Data Lineage, Data Quality, and Data Ownership. - Understanding of DataOps practices, including CI/CD, automated testing, monitoring, logging, and data quality automation. - Experience with Enterprise Architecture frameworks or methodologies such as TOGAF. - Experience working with large-scale data transformation or legacy Data Warehouse modernization programs.
Thông tin tham khảo
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- Nguồn tin
- Nguồn: CareerViet · đăng 14/07/2026
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