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The Role
Lead enterprise data architecture for cloud-native platforms, defining architectural standards, data models, governance frameworks, data mesh and data product patterns. Translate business requirements into scalable designs, oversee metadata, lineage, quality, access controls, and compliance, and guide engineering teams through architecture reviews. Collaborate on feature stores, MLOps, platform innovation, and technology evaluation while mentoring peers and influencing long-term data strategy.
Summary Generated by Built In
About the RoleWe 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
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.
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.
Skills Required
- 9-11 years of experience in Data Architecture or senior Data Engineering, including at least 3 years in an architecture-focused capacity
- Graduate degree in Computer Science, Information Systems, or equivalent
- Strong analytical thinking and logical reasoning
- Ability to communicate complex architectural decisions to technical and non-technical stakeholders
- Hands-on expertise with cloud-native data architecture on Azure or equivalent GCP technologies
- Deep proficiency in data modeling, including lakehouse and medallion architecture patterns
- Experience designing data mesh or data product architectures, including domain ownership, data contracts, and self-service data infrastructure
- Strong knowledge of metadata management, data cataloging, and data lineage tools
- Proficiency in data quality and observability frameworks
- Experience with relational and non-relational databases, data streams, and file stores
- Proficiency in Python and SQL
- Familiarity with version control and CI/CD tools such as GitHub and Jenkins
- Experience defining enterprise data governance frameworks, data stewardship models, and data ownership policies
- Familiarity with GDPR, CCPA, and data privacy or regulatory compliance standards
- Exposure to MLOps platforms and feature stores
- Knowledge of API design and enterprise integration patterns
- Experience integrating reporting and BI tools at the platform architecture layer
- Exposure to DevOps, observability, pipeline monitoring, and data SLA management
- Experience supporting business users and data product teams with architecture guidance
- Ability to produce architecture decision records, design diagrams, and platform standards documentation
- Familiarity with Terraform or Bicep for infrastructure as code
Gap (gapinc.com). Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Gap (gapinc.com). and has not been reviewed or approved by Gap (gapinc.com)..
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is offered, alongside programs that support physical, mental, and financial wellbeing. Feedback suggests eligible employees can also leverage tools like FSAs and additional wellbeing resources.
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Leave & Time Off Breadth — Paid time off, company-paid holidays, and multiple leave options (sick, disability, and family leave) create broad time-away coverage. Some roles start with substantial PTO accrual and can access flexible leave arrangements.
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Wellbeing & Lifestyle Benefits — A generous cross-brand merchandise discount is a standout perk, complemented by commuter benefits, on-the-clock volunteer hours, and matching donations. Feedback suggests these lifestyle benefits add meaningful value beyond base pay.
Gap (gapinc.com). Insights
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The Company
What We Do
In 1969, Don and Doris Fisher opened the first Gap store on Ocean Avenue in San Francisco. They wanted to make it easier to find a great pair of jeans, and they did. Their denim and records store was a hit, and it grew to become one of the world’s most iconic brands. Today we’re represented in more than 1400 stores in over 40 countries, and online. We have headquarters in New York, London, Shanghai, Tokyo, and, of course, San Francisco. Our unique aesthetic is optimistic cool, elevated American style. Our clothes are crafted with care, with focused attention to thoughtful design. We believe in staying true to our heritage while creating what’s next. Don and Doris Fisher always wanted to “do more than sell clothes.” They wanted to support the people who ran their company, to be active in their communities, and to have a positive impact on the world. Their vision helped transform retail, and we’re still following their lead. We stand for freedom and possibility for all; we champion diverse ideas that transcend generations, geographies and genders.
