Enterprise Data Architect

Role Overview

Enterprise Data Architect

1. Enterprise Data Architecture Ownership

• Own end-to-end
• enterprise data architecture
• across Digital Commerce, Retail IT, Supply Chain, CRM, Loyalty, Marketing Tech, Finance, and Data Platforms.
• Define
• current-state, target-state, and transition architectures
• aligned to Landmark’s omnichannel growth and cost-efficiency objectives.
• Ensure data platforms can scale for
• high-volume retail operations, seasonal peaks, and multi-country expansion
• .

2. Omnichannel Data Enablement

• Architect unified data models for
• customer, product, inventory, order, pricing and promotions
• across online and offline channels.
• Enable real-time and near real-time data flows supporting use cases such as:
• Unified inventory & fulfillment visibility
• Customer 360 & personalization
• Omnichannel analytics and reporting
• Support peak traffic events (e.g., festive sales, White Wednesday equivalents) with resilient, scalable data pipelines.

3. Data Platform Modernization

• Lead modernization of data platforms including
• data lakes, data warehouses, streaming platforms and analytics stacks
• .
• Drive adoption of
• cloud-native, API-first, and event-driven data architectures
• .
• Rationalize legacy data stores, point integrations, and duplicated reporting systems across brands.

4. Data Governance, Quality & Compliance

• Define and implement
• enterprise data governance frameworks
• , including:

• Master Data Management

• Metadata management & lineage
• Data quality standards and controls
• Ensure compliance with
• data privacy, PCI, regional regulatory and security requirements
• by design.
• Establish clear data ownership, stewardship and access control models.

5. Business & Leadership Partnership

• Act as a
• strategic advisor
• to Business, Digital, Supply Chain, Finance and Analytics leaders.
• Translate commercial priorities into
• data roadmaps and investment plans
• .
• Enable faster decision-making through trusted, timely, and actionable data.

6. Delivery Assurance & Architecture Governance

• Establish and run

Data Architecture Review Boards (Arb)

• and design authorities.
• Partner with Product, Engineering, Analytics, and SI partners to ensure
• architecture-aligned execution
• .
• Prevent architectural debt, data silos, and uncontrolled proliferation of tools.

7. Vendor & Platform Strategy

• Evaluate and govern
• SaaS platforms, hyperscalers, BI tools and data vendors
• .
• Drive
• vendor consolidation and cost optimization
• across brands and regions.
• Ensure long-term scalability and contractual alignment to target data architecture.

8. Capability Building & CoE

• Build and mentor a

Group Data Architecture And Data Platform Coe

• .
• Upskill teams on modern data architecture, analytics engineering, and governance practices.
• Drive reuse of shared data assets, models, and pipelines across brands.

Experience

• 15+ years in data architecture, enterprise architecture or large-scale analytics platforms.
• Strong experience in
• retail, eCommerce, consumer internet or large enterprise ecosystems
• .
• Proven experience working across
• multi-brand, multi-country environments
• .

Technical Expertise

• Cloud data platforms (AWS / Azure / GCP)
• Data Lake / Lakehouse / Warehouse architectures
• Streaming & event platforms (Kafka, Pub/Sub, Event Hub equivalents)
• BI & Analytics tools
• MDM, metadata, data quality, and governance tools
• Strong understanding of API and integration patterns

Leadership & Behavioral Traits

• Strategic, systems thinker with strong business acumen
• Ability to influence senior stakeholders without direct authority
• Strong governance mindset balanced with speed and pragmatism
• Comfortable operating in ambiguity and scale