Cloud Engineer/ Support Engineer - Cloud

Google Retail Search Engineer Experience : 3–6 years Role Type : Retail Search / Integration Engineer
Role Overview We are looking for a Google Retail Search Engineer to implement and integrate Google Retail Search parallel A/B testing initiative against Elastic Search. The role focuses heavily on product feed ingestion, Google schema mapping, taxonomy/attribute transformation, search API integration, query routing, response transformation, testing and UAT.
Key Responsibilities
- Implement Google Retail Search for the parallel A/B platform.
- Analyze existing product, pricing, inventory, taxonomy and attribute data.
- Map existing product/feed schema to Google Retail Search schema.
- Preserve identifiers, pricing, inventory and business-critical attributes.
- Build feed-generation and transformation processes.
- Extend ingestion pipelines to Google, including batch/full and near-real-time updates where required.
- Integrate Google APIs with Java/microservice applications.
- Contribute to query routing between Google and Elastic.
- Transform Google responses into the existing API/UI format without changing the contract.
- Implement search, filters, facets and autocomplete capabilities.
- Develop data, functional, integration and regression tests.
- Support A/B comparison, discrepancy analysis, UAT and business acceptance.
- Troubleshoot feed, mapping, API and search issues.
- Document mappings, transformations, APIs and test scenarios.
Required Skills
- 3–6 years software/data/search engineering experience.
- Google Cloud experience; Google Retail Search preferred.
- Strong Java and/or Python.
- REST APIs and JSON.
- Data transformation and ingestion pipelines.
- Strong product/catalog, schema, taxonomy and attribute-mapping knowledge.
- Search API integration and troubleshooting.
- Ability to work across data, application and search layers.
Good to Have
- Retail/e-commerce experience.
- Large product catalog / SKU-based search experience.
- Cloud, Docker, Kubernetes and CI/CD knowledge.
- Streaming or near-real-time data pipelines.
- Semantic/vector search experience.
- Generative AI, AI Agents / Agentic AI or AI-assisted engineering experience.
- Experience using AI/agents for test automation, data mapping, search evaluation, troubleshooting or engineering productivity.
- BigQuery, Pub/Sub, Dataflow, Cloud Storage or Cloud Run.
- Elastic Search experience.