Data Architect Senior (TIS-Trib Platforme Date)

Job description

The Enterprise Data Architect is a key member of the Enterprise Architecture Center of Expertise and is responsible for defining, governing and evolving the enterprise data architecture with a strong focus on cloud transformation and modern data platforms The role will play a central part in shaping the bank’s target data platform, ensuring consistency across the existing Exadata-based data warehouse, the Iceberg-based data lake/lake-house layer, and the future Databricks-enabled cloud data platform.

Working closely with the Data & BI teams, Chief Data Officer, enterprise and technical architects, data engineers, and delivery teams, the Data Architect will play an important role in integrating the Data Lake platform with the Cloud, will define the target architecture, architecture principles, migration patterns and ensures alignment with BRD’s business strategy through the migration and modernization journey.

Job Description

Define and evolve the enterprise data architecture strategy aligned with business priorities, data strategy and cloud transformation objectives Contribute to enterprise-wide cloud strategy, ensuring alignment between data, application, and infrastructure architectures. Ensure architectural alignment between the existing Exadata environment, the Iceberg-based data-lake platform, and the future Databricks implementation.

Support the integration of the on-premises Data Lake with the cloud, including assessment of the current state assessment, definition of the target architecture and the migration strategy and the definition of data ingestion, processing, storage, and consumption patterns in the cloud environment In an Agile setup, help the teams translate business requirements into high-level data and cloud architecture solutions, to define data models, flows, integration patterns, and cloud services usage, assess impact on existing systems and define transition architectures.

Ensure adherence to architecture principles and cloud governance policies.

• Define the integration of data governance frameworks into cloud architecture: Metadata management, data lineage, cataloging, Data quality controls, Reference Data Management, Data classification and access policies
• Drive adoption of Cloud-native architectures, Event-driven and streaming data pipelines, DataOps and CI/CD for data pipelines
• Evaluate emerging trends such as Data Mesh, Data Fabric, AI/ML enablement on data platforms
• Provide recommendations on tools, frameworks, and platforms aligned with enterprise standards.

Provide recommendations about, and define, Applicative Data Layers and data flows moving data between layers Present and validate solutions in Architecture Committees Act as a subject matter expert for data and architecture