Enterprise Data Architect

Job description

DBiz is seeking an experienced Enterprise Data Architect ton behalf of one of our enterprise clients. This is a strategic architecture role responsible for defining and governing the organization's enterprise data landscape, ensuring data platforms are scalable, secure, well-governed and aligned with business objectives.

While Snowflake is the client's primary cloud data platform, the successful candidate will possess broad expertise across modern enterprise data technologies and architecture practices. The role requires someone who can think beyond a single platform, providing architectural leadership across cloud data platforms, integration, analytics, governance and emerging AI capabilities.

Working closely with Enterprise Architecture, Business, Digital, Security, Data Engineering and Analytics teams, you will establish enterprise-wide data standards, drive architectural decisions and support the delivery of modern, data-driven solutions.

Key Responsibilities

Enterprise Data Architecture

• Define and maintain the enterprise data architecture roadmap aligned to business and technology strategy.
• Develop enterprise data principles, standards and reference architectures.
• Provide architectural leadership across strategic transformation initiatives.
• Collaborate with Enterprise Architects to ensure alignment with the broader technology landscape.
• Participate in architecture governance and review boards.

Snowflake Architecture

• Lead the architecture and governance of the enterprise Snowflake platform.
• Design secure, scalable and high-performing Snowflake solutions.
• Establish best practices for:
• Data modelling
• Performance optimization
• Security and RBAC
• Data Sharing
• Virtual Warehouses
• Cost optimization
• Snowpark
• Streams and Tasks
• Time Travel and Zero Copy Cloning

Enterprise Data Platforms

Design and provide architectural guidance across modern enterprise data technologies, including:

• Snowflake
• Microsoft Fabric
• Azure Data Platform
• Azure Data Lake
• Azure Synapse Analytics
• Databricks
• SQL Server
• Lakehouse architectures
• Data Lakes
• Data Fabric and Data Mesh concepts

Data Integration

Provide architectural oversight across enterprise integration capabilities including:

• REST APIs
• Event-driven architecture
• Kafka
• Azure Event Hub
• Azure Data Factory
• ETL/ELT frameworks
• Streaming and batch data pipelines

Data Governance

Partner with business and technology teams to establish enterprise-wide governance practices covering:

• Data Quality
• Metadata Management
• Master Data Management (MDM)
• Data Lineage
• Data Classification
• Privacy and Security
• Information Lifecycle Management

Analytics and AI Enablement

Design data architectures that support:

• Enterprise reporting
• Self-service analytics
• Power BI
• Microsoft Fabric Analytics
• AI and Machine Learning initiatives
• Generative AI use cases through trusted enterprise data

Cloud Architecture

Provide strategic guidance across cloud-based data platforms, ensuring:

• Scalability
• Security
• Resilience
• Cost optimization
• Operational excellence
• Future readiness

Essential Skills & Experience

Enterprise Architecture

• 10+ years of experience in Enterprise Data Architecture, Data Platform Architecture or Solution Architecture.
• Demonstrated experience designing enterprise-scale data ecosystems.
• Strong understanding of enterprise architecture principles and governance.

Snowflake

Extensive hands-on architecture experience including:

• Snowflake platform architecture
• Performance tuning
• Security architecture
• Data Sharing
• Snowpark
• Streams and Tasks
• Cost optimization
• Governance

Modern Data Platforms

Strong experience across several of the following:

• Microsoft Fabric
• Azure Synapse Analytics
• Azure Data Factory
• Azure Data Lake Storage
• Databricks
• SQL Server
• Lakehouse architectures
• Data Mesh
• Data Fabric

Integration

Experience designing enterprise integration solutions using:

• APIs
• Event-driven architectures
• Kafka
• Azure Integration Services
• Streaming technologies
• ETL and ELT frameworks

Data Modelling

Strong understanding of:

• Dimensional modelling
• Data Vault
• Kimball methodology
• Canonical data models
• Logical and physical data modelling

Governance & Security

Experience implementing enterprise data governance practices, including:

• Data Quality
• Metadata Management
• MDM
• Data Lineage
• Information Security
• Compliance frameworks

Cloud Technologies

Experience with:

• Microsoft Azure
• Cloud-native data architectures
• Infrastructure as Code
• CI/CD and DevOps practices

Desirable Skills

• Experience within large enterprise or regulated environments.
• Familiarity with Microsoft Purview or similar data governance platforms.
• Exposure to AI-ready data architectures.
• Experience implementing Microsoft Fabric alongside Snowflake.
• Knowledge of modern enterprise integration and analytics ecosystems.