Job Description & Details
The retail sector is undergoing a data‑driven transformation, and companies need architects who can turn chaotic data into strategic assets. This role blends deep retail domain knowledge with AWS expertise to build scalable, AI‑ready pipelines. If you love shaping data foundations that power next‑gen commerce, this Data Architect position is a perfect fit.
Job Summary
You will design a canonical domain model for core retail entities, create robust data pipelines linking ERP, OMS, CRM, and pricing systems, and build infrastructure ready for AI/ML workloads. The role also involves leading brand migrations, authoring architecture decision records, and collaborating closely with the Platform Architecture Lead as the data domain expert.
Top 3 Critical Skills Table
| Skill | Why it's critical | Mastery Level |
|---|---|---|
| Data Modeling & Canonical Domain Design | Ensures consistent product, order, and customer data across all brands, reducing duplication and errors. | Senior |
| AWS Cloud Architecture (e.g., Redshift, S3, Glue, Lake Formation) | Powers scalable, secure, and cost‑effective data pipelines and AI/ML feature stores. | Senior |
| Retail Domain Knowledge (ERP, OMS, Pricing, Inventory) | Allows you to map complex retail processes to a unified data model and drive successful migrations. | Senior |
Interview Preparation
- How would you design a canonical data model for retail entities like Product, Order, and Customer?
What the interviewer is looking for: Ability to identify core attributes, relationships, and normalization strategies that support multiple brands. - Explain how you would build a data pipeline on AWS to ingest clickstream data for downstream ML models.
What the interviewer is looking for: Knowledge of services such as Kinesis, S3, Glue, and how to ensure low‑latency, fault‑tolerant ingestion. - What steps would you take to ensure PII governance and data lineage in a multi‑tenant environment?
What the interviewer is looking for: Understanding of encryption, access controls, Lake Formation tags, and lineage tracking tools. - Describe a migration strategy you would use to move a legacy brand’s data into the new canonical model.
What the interviewer is looking for: Experience with workshops, gap analysis, automated ETL, and ADR documentation. - How do you balance performance vs. cost when designing feature stores for AI/ML workloads on AWS?
What the interviewer is looking for: Insight into partitioning, storage tiering, query optimization, and cost‑monitoring practices.
Resume Optimization
- Data Architect
- Retail Data Modeling
- AWS Redshift / S3 / Glue
- Canonical Domain Model
- Data Pipelines (ERP, OMS, CRM)
- AI/ML Feature Store
- PII Governance
- Data Lineage
- Brand Migration
- Architecture Decision Records (ADRs)
Application Strategy
When emailing the recruiter, start with a brief greeting, attach your resume, and clearly highlight how your background aligns with the role. Mention your top skills such as AWS data engineering, retail domain modeling, and brand migration experience. Reference specific projects where you built end‑to‑end pipelines or led data‑model standardization, and close by expressing enthusiasm for contributing to their data platform.
Career Roadmap
| Current Role | Typical Experience | Core Focus | Next Position |
|---|---|---|---|
| Data Architect | 5‑7 years, retail & AWS | Canonical modeling, pipeline design, governance | Senior Data Architect |
| Senior Data Architect | 8‑10 years, cross‑domain leadership | Strategic data platform, AI/ML enablement | Data Platform Lead |
| Data Platform Lead | 10+ years, end‑to‑end ownership | Organization‑wide data strategy, team management | Director of Data Engineering |