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The Role
Build and maintain GCP-based data pipelines, data products, and AI/ML applications using services including BigQuery, Vertex AI, Dataflow, and Dataproc. Develop transformations with Python, SQL, and PySpark; implement CI/CD, monitoring, testing, and observability; ensure data quality and reliability; troubleshoot pipeline issues; and support stakeholders with data requirements, analytics, and reporting.
Summary Generated by Built In
About the RoleWe are hiring a Senior Software Engineer (G6) to build and deliver intelligent, cloud-native data solutions on Google Cloud Platform (GCP) at Gap Inc. In this role, you will develop robust data pipelines and AI/ML-powered applications that enable smarter decision-making across our global retail operations. You will work hands-on with GCP-native services and modern AI frameworks, collaborate closely with cross-functional teams, and contribute to engineering best practices within GapTech's growing Hyderabad hub.
This role is ideal for engineers passionate about cloud data engineering and applied AI who want to build production-grade systems that create real business impact for iconic global brands.What You'll Do
This role is ideal for engineers passionate about cloud data engineering and applied AI who want to build production-grade systems that create real business impact for iconic global brands.What You'll Do
- Design, develop, and maintain GCP-based data pipelines integrating multiple business applications and data sources.
- Build and deploy AI/ML models and data products using GCP AI services (Vertex AI, BigQuery ML, Gemini APIs).
- Develop data transformation logic using PySpark, SQL, and Python on GCP platforms (Dataflow, Dataproc, BigQuery).
- Work within a DevOps environment with CI/CD pipelines, automated deployments, and cloud-native monitoring.
- Participate in code reviews, uphold coding standards, and ensure data quality and pipeline reliability.
- Perform root cause analysis on data issues and implement robust, long-term solutions.
- Support business stakeholders with data requirements, analytics insights, and reporting needs.
- Contribute to improving automation, testing, and observability practices across the data platform.
- 4–7 years of overall experience, with at least 3+ years in a Data Engineering or Cloud AI role.
- Graduate degree in Computer Science, Engineering, or equivalent.
- Mandatory: Hands-on expertise with GCP data and AI services:
- BigQuery — data modeling, optimization, partitioning, and clustering
- Vertex AI — model training, deployment, and MLOps pipelines
- Cloud Dataflow / Dataproc — batch and streaming data processing
- Cloud Composer (Apache Airflow) — pipeline orchestration
- Cloud Storage, Pub/Sub, and Bigtable — data storage and real-time streaming
- Mandatory: Experience building and operationalizing AI/ML models in GCP (Vertex AI, BigQuery ML, or Generative AI APIs).
- Proficiency in Python and SQL for data engineering and AI/ML workflows.
- Familiarity with PySpark for large-scale data transformations.
- Strong understanding of data pipeline architecture — batch, micro-batch, and streaming patterns.
- Experience with version control and CI/CD tools (GitHub, Cloud Build, Jenkins).
- Proficiency in Linux shell scripting and automation.
Good-to-Have Skills
- Experience with LLM integration or Generative AI on GCP (Gemini APIs, Model Garden, or similar).
- Familiarity with data governance, data cataloging (Dataplex), and data lineage on GCP.
- Exposure to dbt (data build tool) for transformation and documentation.
- Knowledge of enterprise integration patterns and event-driven architectures.
- Experience with BI and reporting tools such as Looker, Power BI.
- Strong communication and stakeholder collaboration skills in cross-functional, global teams.
Skills Required
- 4-7 years of overall professional experience
- At least 3 years of experience in data engineering or cloud AI
- Graduate degree in Computer Science, Engineering, or equivalent
- Hands-on experience with BigQuery, including data modeling, optimization, partitioning, and clustering
- Experience with Vertex AI for model training, deployment, and MLOps pipelines
- Experience with Cloud Dataflow and Dataproc for batch and streaming processing
- Experience with Cloud Composer and Apache Airflow for pipeline orchestration
- Experience with Cloud Storage, Pub/Sub, and Bigtable
- Experience building and operationalizing AI/ML models using Vertex AI, BigQuery ML, or generative AI APIs
- Proficiency in Python and SQL
- Familiarity with PySpark
- Understanding of batch, micro-batch, and streaming data pipeline architectures
- Experience with version control and CI/CD tools such as GitHub, Cloud Build, or Jenkins
- Proficiency in Linux shell scripting and automation
- Experience with LLM integration or generative AI on GCP
- Familiarity with data governance, data cataloging, and data lineage on GCP
- Exposure to dbt
- Knowledge of enterprise integration patterns and event-driven architectures
- Experience with Looker or Power BI
- Strong communication and stakeholder collaboration skills
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.
