We are seeking a strategic and hands-on Enterprise Data Architect to lead the assessment and transformation of a large retail industry client’s data architecture to support enterprise-wide AI initiatives . This advisory consulting role requires working closely with C-suite stakeholders, business leaders, and technical teams to define a future-state data architecture that enables advanced analytics, machine learning, and AI at scale.

The ideal candidate will have deep expertise in enterprise data strategy, architecture design, and data modernization , with a strong understanding of AI/ML platforms and real-world experience in retail, supply chain, or customer engagement domains .

• Engage with executive stakeholders to understand business strategy, objectives, and data-driven transformation goals.
• Lead discovery sessions to assess the current data landscape : sources, platforms, pipelines, data governance, security, and analytics maturity.
• Define and document current-state architecture including pain points, redundancies, and limitations.
• Develop and present a future-state data architecture roadmap tailored for AI enablement —including data fabric, lakehouse, real-time streaming, and cloud-native capabilities.
• Identify and recommend foundational capabilities needed to support AI/ML, including data quality, master data management, metadata, lineage, and governance .
• Provide architectural guidance on cloud platforms (e.g., AWS, Azure, GCP) and AI/ML services that align with enterprise requirements.
• Collaborate with client’s technical teams to ensure feasibility and alignment of proposed solutions.
• Recommend best practices around data democratization, federated data access, and responsible AI .
• Support business case development including value realization mapping and prioritization of initiatives.
• Facilitate executive briefings and technical design workshops to align strategy, architecture, and execution.

• 10+ years in enterprise data architecture or data strategy consulting , with a strong focus on retail industry use cases.
• Proven ability to work in client-facing advisory roles interacting with executive leadership and technical stakeholders .
• Deep understanding of modern data architecture concepts , including:
• Data lakehouse, data mesh, and data fabric
• Cloud-native data platforms (Databricks, Snowflake, BigQuery, Redshift, Synapse)
• Real-time data ingestion (Kafka, Kinesis, Spark Streaming)
• API-first integration models and data virtualization
• Strong knowledge of AI/ML data requirements (e.g., feature stores, model training pipelines, data versioning, labeling).
• Familiarity with enterprise data governance , including regulatory compliance (GDPR, CCPA), data cataloging, and metadata management.
• Experience designing hybrid or multi-cloud architectures and aligning with enterprise security and compliance standards.
• Exceptional communication and presentation skills for C-level audiences.
• Strong analytical mindset and the ability to distill complex concepts into actionable recommendations.

• Retail industry expertise in domains such as customer analytics, personalization, supply chain optimization, or inventory intelligence .
• Prior experience with enterprise AI transformations , particularly in large-scale environments.
• Cloud certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate, GCP Professional Data Engineer).
• TOGAF, DAMA CDMP, or equivalent data architecture certifications.
• Experience working in or alongside large consulting firms (Big 4, Tier 1 systems integrators) is a strong plus.
• Familiarity with responsible AI frameworks and data ethics practices is desirable.

You’ll play a pivotal role in shaping the AI-driven future of a global retail enterprise, helping them modernize their data foundation and unlock new opportunities across customer experience, operations, and innovation.

This is an opportunity to lead at the intersection of business and technology , advising senior leaders on how to turn data into strategic value through thoughtful architecture and AI readiness.