VBeyond Corporation · IT Recruiter
Job Description :-
Data Architect with strong Retail and AWS Experience
Own the data layer of a multi-tenant ecommerce platform running commercially competing retail brands on shared infrastructure. The core challenge is designing data isolation across brands sharing the same platform while meeting PCI-DSS and GDPR compliance requirements for cardholder data and customer PII.
What you'll do:
Design and enforce the canonical domain model (Product, Order, Customer, Cart, Inventory, Price, Payment) that all brands conform to
Design the data pipelines connecting enterprise systems (ERP, OMS, Inventory, CRM, Pricing, payments) to the platform
Design the data infrastructure to support future AI/ML workloads — tenant-partitioned feature stores, clickstream capture, entity resolution, data lineage, and PII governance
Lead brand migration. Facilitate workshops with brand teams and upstream system owners to map existing data to the canonical model, identify gaps, and agree the migration path & data migration automation
Present data architecture decisions as formal ADRs to the Architecture Review Board
Partner with the Platform Architecture Lead as the data domain expert — drive the data workstream independently
Tech stack:
AWS, AWS (RDS PostgreSQL, ElastiCache, S3, EventBridge, Glue, DMS), Datastax Astra, Neptune, SageMaker Feature Store, EMR, Snowflake
What you bring:
Multi-tenant data isolation at scale
Event-driven architecture and change data capture pipeline engineering
Ecommerce domain modeling across order management, inventory, and pricing
Snowflake or equivalent data warehouse/lakehouse technologies . schema design, partitioning strategies, and query optimization
PCI-DSS and GDPR data compliance . classification, encryption, access controls, and audit trails for cardholder data and customer PII
Java and Python proficiency
AI/ML foundational knowledge . understanding of feature engineering, data pipelines for model training, and how data architecture decisions enable or constrain ML workloads
• Experience driving cross-team alignment and architecture decisions through formal review
Expert and leadership (8+years)
Data Modeling
ETL Processes
SQL
Cloud Platforms
Data Warehousing
Big Data Technologies
Data Governance
Staffing and Recruiting·201-1,000 employees
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