Enterprise Data Architect
6+ months
Hybrid – Atlanta, GA
Client domain: Retail
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.
Key Responsibilities:
- 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.
Required Skills & Qualifications:
- 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.
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