Data Architect

Job Title: Data Architect

Location: Lake Forest, IL (Onsite once every 2 months)

Data Architect Retail Data Integration & Single Source of Truth

This role requires a unique combination of retail domain knowledge, data architecture expertise, cloud data platform experience, and stakeholder management capabilities.

Key Responsibilities

Retail Data Strategy & Architecture

• Assess retailer data sources and current-state architecture.
• Define a target-state enterprise retail data architecture.
• Design a common retail data model (Canonical Data Model).
• Establish a scalable "Single Source of Truth" framework.
• Create data integration standards across retailer ecosystems.

Retail Data Integration

• Lead integration of retailer data feeds including:
• Walmart Scintilla/Luminate
• Target RBD/VIQ
• Kroger 84.51 / Stratum
• Sam's Club MAP
• Additional retailer data sources
• Design ingestion patterns for:
• APIs
• Flat files
• EDI feeds
• SFTP integrations
• Data subscriptions

Data Modeling

• Design enterprise-wide:
• Product hierarchy models
• Inventory models
• Customer/Retailer models
• Store hierarchy models
• Supply chain models
• Sales and demand models
• Create canonical definitions for:
• Sell-through
• On-hand inventory
• In-transit inventory
• Weeks of supply
• Fill rate
• OTIF
• Forecast accuracy

Data Governance

• Define data quality framework.
• Establish KPI governance.
• Design metadata management processes.
• Create business glossary and data catalog structures.
• Support Master Data Management (MDM) strategy.

Analytics Enablement

• Architect data structures supporting:
• Power BI
• Tableau
• Executive dashboards
• Commercial analytics
• Supply chain analytics
• AI/ML use cases

Must-Have Retail Experience

Mandatory

Retail / CPG Experience

10+ years working in:

• Consumer Packaged Goods (CPG)
• Retail Analytics
• Retail Supply Chain
• Retail Data Platforms

Must-Have Technical Capabilities

1. Data Architecture

Expert Level

• Enterprise Data Architecture
• Data Lake Architecture
• Lakehouse Architecture
• Data Warehouse Architecture
• Canonical Data Modeling
• Dimensional Modeling (Star Schema)
• Data Vault 2.0 (preferred)

Deliverables Expected

• Conceptual Data Model
• Logical Data Model
• Physical Data Model
• Enterprise Data Flow Architecture

2. Cloud Data Platforms

Must Have

Experience with at least one:

• Microsoft Azure (Preferred)
• AWS
• Google Cloud

Strong Preference

Azure Stack:

• Azure Data Factory
• Azure Synapse
• Azure Data Lake Gen2
• Microsoft Fabric
• Azure Databricks
• Azure SQL

3. Data Engineering & Integration

Must Have

• ETL / ELT Architecture
• API Integration
• Event-driven Architecture
• Batch Processing
• Data Pipeline Design

Tools:

• Azure Data Factory
• Databricks
• Informatica
• Talend
• SSIS
• Kafka (preferred)

4. Retail Data Modeling Expertise

Candidate must understand:

Inventory Metrics

• On-Hand Inventory
• Available Inventory
• Safety Stock
• In-Transit Inventory
• Weeks of Supply

Sales Metrics

• POS Sales
• Sell-In
• Sell-Through
• Unit Velocity

Supply Chain Metrics

• OTIF
• Fill Rate
• Forecast Accuracy
• Replenishment Metrics

5. Data Governance & MDM

Must Have

• Data Quality Frameworks
• Data Lineage
• Metadata Management
• Master Data Management
• Data Catalog Implementation

Tools preferred:

• Microsoft Purview
• Collibra
• Alation

6. Analytics & Reporting

Must Have

Understanding of:

• Power BI
• Tableau
• Semantic Models
• KPI Framework Design
• Executive Dashboards

7. AI & Advanced Analytics (Preferred)

Experience enabling:

• Demand Forecasting
• Inventory Optimization
• Predictive Analytics
• Machine Learning Data Platforms
• GenAI-enabled Insights

Preferred technologies:

• Azure AI Services
• Azure Machine Learning
• Databricks ML

Soft Skills / Consulting Skills

Must Have

• Executive stakeholder management
• CTO/CIO level communication
• Retail business process understanding
• Workshop facilitation
• Architecture governance
• Vendor management

Ability to translate:

Retail Business Problem Data Architecture Technology Solution Business Outcome

Ideal Candidate Profile

Experience

• 12-15+ years overall experience
• 5+ years as Lead Data Architect
• Retail/CPG domain experience
• Large-scale enterprise data platform implementations

What Success Looks Like in the First 90 Days

1. Assess all retailer data sources and current architecture.
2. Define a Retail Canonical Data Model.
3. Produce target-state architecture and roadmap.
4. Create retailer-to-canonical mapping framework.
5. Define enterprise KPI definitions.
6. Deliver MVP architecture and Target integration.
7. Establish foundation for a Retail Single Source of Truth platform.

One-Line Requirement

"We need a Data Architect who has previously built a unified retail data platform across multiple retailer ecosystems and can rapidly design a scalable Single Source of Truth architecture for commercial, inventory, and supply chain analytics."