Snowflake Data Architect

Job Summary

☑ Level of Education

• Bachelor’s degree with 10+ years within Digital & Technology environment and within E2E supply chain.
• Strong skills in managing and building Data Products and designing Data Architecture for large enterprises.

☑ Experience

• Strong hands-on experience in SQL, relational databases, data exploration, and Business Intelligence tools (Tableau, Power BI, or equivalent).
• Proven ability in logical problem-solving, data design, and analytical thinking, with working exposure to Python or similar scripting languages preferred.
• Advanced proficiency in Excel for data analysis, validation, and dashboard-ready presentations.
• Solid experience ensuring data quality, integrity, and compliance across enterprise reporting and data products.
• Hands-on domain experience across Demand, Supply, Inventory Planning, Logistics Operations, and Manufacturing within Pharma / Consumer Health environments.
• Strong understanding of planning, data management, order management, logistics execution, and visualization platforms.
• Excellent communication and stakeholder management skills, with the ability to influence and collaborate across global, multi-level stakeholders.

Key Responsibilities

Data Architecture Design & Data Product Delivery (BUILD)         

• Design scalable, reusable data architectures for Global Logistics domains (shipments, lanes, carriers, inventory, cost, compliance) and define Data models, products aligned with Enterprise

• Lead end-to-end delivery of logistics data products development

• Translate business requirements into technical architecture

Data Quality, Operational Stability & Reliability (MAINTAIN)      

• Own data quality, availability, and freshness of logistics data assets. Implement monitoring, alerting, and remediation frameworks

• Reduce recurring data issues and manual reconciliations

• Ensure stable operation of data pipelines with partners

System & Vendor Integration (INTEGRATE)         

• Architect and manage integrations between TMS, WMS, ERP, IoT and external partners (3PLs, carriers, customs brokers)

• Enable API-based, event-driven, and batch integrations

Data Enablement for Analytics & AI (INTEGRATE)

• Enable consumption of Logistics data for AI/ML, Analytics

• Partner with Analytics, Product, and Digital Teams for Insights

Legacy Modernization & Migration (EXIT)          

• Lead data migration strategies during system modernization

• Ensure no business disruption or data loss during transitions

Technology Rationalization (EXIT)            

• Identify opportunities to decommission obsolete data assets and pipelines & reduce technical debt and platform sprawl.

• Support business cases for platform consolidation & optimal costs

Governance & Compliance         

• Ensure data architecture complies with GxP, SOx, Audit needs

• Enforce metadata, lineage, access, and retention standards.

• Act as a gatekeeper for architecture quality

Team Leadership, Capability Building & Stakeholder Partnership  • Mentor and guide Senior Associates and technical contributors.

• Provide architectural direction and design reviews.

• Serve as a trusted data architecture partner

Skill Requirements

 ☑ Languages

• English

☑ Computer Skills

• Strong proficiency in SQL, relational databases, and data querying.
• Strong experience with Business Intelligence tools (Power BI, Tableau).
• Python or other scripting languages and cloud data platforms.
• Advanced skills in Microsoft Excel and presentation tools for analytics communication.
• Hands-on experience in:
• Tableau (Must)
• Python (Must)
• DATAIKU (Must)
• SQL
• Database Management
• Query Languages

Additional Preferred Skills

• Data Architecture and Data Product Management
• Enterprise Data Modeling
• Supply Chain & Logistics Analytics
• Cloud-Based Data Platforms
• Data Governance and Compliance (GxP, SOX)
• Stakeholder Management and Cross-Functional Collaboration
• AI/ML Data Enablement and Analytics Integration

Other Requirements

• Data Architecture and Data Product Management
• Enterprise Data Modeling
• Supply Chain & Logistics Analytics
• Cloud-Based Data Platforms
• Data Governance and Compliance (GxP, SOX)
• Stakeholder Management and Cross-Functional Collaboration
• AI/ML Data Enablement and Analytics Integration