About the Role
We are hiring a Staff Data Architect to shape the future of data architecture at Gap Inc. In this role, you will define and govern the architectural standards, patterns, and blueprints that underpin our cloud-native data platform — powering decision-making across our global retail business. You will work hands-on with technologies like Databricks, dbt, Azure/GCP cloud platforms, and GenAI-powered solutions while mentoring peers, driving architectural best practices, and influencing the long-term data strategy for our iconic brands.
This role is ideal for architects who thrive on solving complex data design challenges, translating business needs into scalable technical blueprints, and continuously pushing the boundaries of data modelling, governance, and platform innovation. As part of GapTech's growing Hyderabad hub, you will play a critical role in defining the next generation of data architecture that fuels our global retail brands.
What You'll Do
- Define and maintain enterprise data architecture blueprints, reference architectures, and design standards across cloud-native data platforms.
- Partner with Product Managers, Data Engineering leads, and Solution Architects to translate business requirements into scalable, future-proof data designs.
- Lead the architecture and governance of data domains including data modelling, data mesh / data product design, and metadata management.
- Define and enforce data modelling standards (conceptual, logical, physical) across relational, dimensional, and NoSQL stores.
- Collaborate with Data Scientists and ML Engineers to architect feature stores, MLOps pipelines, and model-serving data layers.
- Establish and govern data quality frameworks, lineage tracking, and cataloging standards across the platform.
- Guide engineering teams on applying architectural patterns, data design principles, and platform conventions.
- Conduct architecture reviews and provide design authority sign-off on high-impact data solutions.
- Drive continuous improvement in data platform design, documentation, and reusability of architectural assets.
- Work closely with security and compliance teams to embed data governance, access control, and regulatory standards into platform design.
- Evaluate and recommend emerging technologies and architecture patterns that improve platform capabilities.
Who You Are
Must-have skills
- 9–11 years of experience in a Data Architecture or senior Data Engineering role, with at least 3 years in an architecture-focused capacity.
- Graduate degree in Computer Science, Information Systems, or equivalent.
- Strong analytical thinking, logical reasoning, and the ability to communicate complex architectural decisions to both technical and non-technical stakeholders.
- Hands-on expertise with cloud-native data architecture on:
- Azure: Databricks, Data Lake Gen2, Unity Catalog, Azure SQL, Synapse Analytics, ADF
- Or equivalent GCP stack: BigQuery, Dataflow, Cloud Composer, Dataplex, etc.
- Deep proficiency in data modelling —lakehouse / medallion architecture patterns.
- Experience designing data mesh or data product architectures — including domain ownership, data contracts, and self-serve data infrastructure.
- Strong knowledge of metadata management, data cataloging, and data lineage tools (e.g. Apache Atlas, Alation, DataHub, Unity Catalog).
- Proficiency in data quality and observability frameworks (e.g. Great Expectations, dbt tests, Monte Carlo).
- Experience with relational and non-relational databases, data streams, and file stores.
- Proficiency in Python and SQL for prototyping and validating architectural designs.
- Strong familiarity with version control and CI/CD tools (GitHub, Jenkins) in the context of DataOps and infrastructure-as-code.
Good-to-have skills
- Experience defining enterprise data governance frameworks including data stewardship models and data ownership policies.
- Familiarity with data privacy, regulatory compliance standards (GDPR, CCPA) and their architectural implications.
- Exposure to MLOps platforms and feature stores (Feast, Tecton, Vertex AI Feature Store).
- Knowledge of API design and enterprise integration patterns for data product exposure.
- Experience with reporting and BI tool integration (Power BI, Looker, MicroStrategy) at the platform architecture layer.
- Exposure to DevOps and observability practices including pipeline monitoring and data SLA management.
- Experience supporting business users and data product teams with architecture guidance and patterns.
- Strong documentation skills — ability to produce clear architecture decision records (ADRs), design diagrams, and platform standards documentation.
- Familiarity with infrastructure-as-code tools (Terraform, Bicep) for data platform provisioning.