Senior Enterprise Data Architect

Senior Enterprise Data Architect

Role Summary

The Senior Enterprise Data Architect will play a critical role in advancing Ralph Laurens Enterprise Data & AI Architecture by defining operationalizing and actively implementing enterprise data architecture standards reference patterns and platform guardrails.

This role combines strategic architecture leadership with hands-on execution partnering directly with engineering and delivery teams to design scalable data solutions accelerate adoption of enterprise patterns and enable data-driven transformation across ERP analytics modernization and AI initiatives.

The architect will act as a practitioner-leader ensuring that enterprise architecture principles translate into working solutions reusable assets and measurable acceleration in delivery.

Key Responsibilities

1. Enterprise Data Architecture (Strategy Hands-on Design)

• Define and evolve enterprise data architecture principles standards and target-state models aligned with RL transformation priorities (ERP AI omnichannel).
• Create and contribute hands-on to conceptual logical and canonical data models ensuring alignment across domains.
• Actively support domain teams in designing scalable data models and pipelines not just reviewing them.
• Establish domain boundaries conformed entities and authoritative data ownership models.

2. Reference Architecture & Reusable Patterns (Build Implement)

• Define and implement reusable reference architectures and design patterns across:
  • Data ingestion (batch streaming event-driven)
  • Transformation pipelines
  • Lakehouse and semantic serving layers
• Develop working reference implementations / accelerators (e.g. templates sample pipelines reusable frameworks).
• Partner with engineering teams to embed patterns directly into delivery pipelines.

3. Data Product Architecture (Execution-Oriented)

• Define and operationalize the enterprise data product model including ownership lifecycle and product contracts.
• Actively guide teams in building production-grade data products aligned to enterprise standards.
• Establish hands-on frameworks for:
  • Data product onboarding
  • Trust models (data quality lineage SLAs)
• Enable federated architecture while ensuring enterprise-level consistency.

4. Toolchain & Platform Standards (Hands-on Governance)

• Define and enforce architecture standards across RL data platforms:
  • Databricks (Lakehouse Unity Catalog)
  • Microsoft Fabric (Semantic layer Power BI)
  • SAP Datasphere / BDC
• Work hands-on with teams to:
  • Design data pipelines and platform integrations
  • Implement governance constructs (metadata lineage data quality)
• Drive architecture lifecycle using LeanIX and ADRs to ensure traceability and governance compliance.

5. Strategic Program Architecture (Embedded Delivery Support)

• Embed within key transformation programs (ERP Data Platform AI initiatives) to:
  • Translate enterprise architecture into implementable designs
  • Resolve cross-domain design challenges
• Provide hands-on solution architecture support for critical programs requiring integration across systems data and analytics layers.
• Ensure reuse of enterprise patterns to reduce duplication and technical debt.

6. Architecture Governance & Review (Enable Not Gate)

• Participate in EA governance forums (EAC LEAB TDA).
• Perform pragmatic design reviews with actionable guidance not theoretical feedback.
• Support:
  • Architecture compliance reviews (ACR)
  • Exception management via ADRs
• Act as an enabler to delivery teams ensuring architecture acceleratesnot blocksexecution.

Required Qualifications

• 8 years of experience in Enterprise Data Architecture Data Engineering or Solution Architecture within modern data ecosystems.
• Strong hands-on expertise in:
  • Data modeling (conceptual logical canonical dimensional)
  • Data engineering patterns (batch streaming event-driven)
• Experience building enterprise-scale data platforms and data products.
• Deep familiarity with modern data platforms such as:
  • Databricks Azure / Microsoft Fabric Snowflake SAP Datasphere/BDC
• Proven experience implementing:
  • Metadata lineage data quality governance frameworks
• Strong ability to work directly with engineering teams and influence delivery outcomes

Preferred Qualifications

• Experience supporting ERP (SAP S/4HANA) transformations and data transformations
• Knowledge of API/event-driven integration patterns across operational and analytical ecosystems
• Experience in retail / consumer / omnichannel environments
• Experience with:
  • Semantic layer design and KPI governance
  • AI/ML and GenAI data enablement
• TOGAF DAMA (CDMP) or equivalent certifications

Success Measures (Outcome-Focused)

• Adoption of reusable data architecture patterns across domains
• Reduction in data duplication and technical debt
• Improved time-to-delivery through reusable architectures and paved paths
• Increased trust in enterprise data (quality lineage governance)
• Measurable acceleration in delivery of ERP analytics and AI use cases

Required Skills:

Databricks Microsoft Fabric/Azure Data Modeling Data Engineering Data Products Metadata Lineage Data Governance