> Markdown version of [/jobs/ext/4683888-partner-solutions-architect-ecosystem-engineer-data-systems](https://www.wearedevelopers.com/jobs/ext/4683888-partner-solutions-architect-ecosystem-engineer-data-systems). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Partner Solutions Architect, Ecosystem Engineer Data Systems - **Company:** Google LLC - **Location:** Austin, TX, United States - **Experience:** Expert - **Salary:** $183,000 - $265,000 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Java (Programming Language), Artificial Intelligence, Data Analysis, BigQuery, Software as a Service, Cloud Computing, Databases, Data Architecture, Data Systems, Data Flow Control, Python (Programming Language), Oracle (Applications), Cloud Services, Gemini Enterprise (Agent Platform), Azure Machine Learning, SQL Databases, Systems Integration, Teradata SQL, Enterprise Data Management, Software Repository, Google Cloud, Large Language Models, Snowflake, Apache Spark, Multi-Cloud, Agentic-AI, Data Layers, Information Technology, Data Analytics, Non-relational Database, Model Context Protocol, Looker Analytics, Data Pipelines, Databricks, Golang, Agent2Agent Protocol - **Published:** November 12, 2026 - **Apply:** https://dejobs.org/x/x/98995AAA8D3E4ED8BC6155B860DA1734/job/ ## About the Role Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain., * Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience. * 7 years of experience in customer or partner-facing technical roles such as Solutions Architect, Partner Engineer, Customer Engineer, or Principal Data Architect in a cloud computing environment. * Experience with enterprise data platforms, analytical data warehousing, relational and non-relational databases, and real-time data pipelines (e.g., BigQuery, Spanner, AlloyDB, Pub/Sub, Dataflow, Spark, or equivalent cloud data services). * Experience building solutions with Large Language Models (LLMs), agentic frameworks (e.g., Google ADK, LangGraph), or Retrieval-Augmented Generation (RAG) architectures using Python, SQL, Go, or Java., * Experience developing Model Context Protocol (MCP) servers, Agent-to-Agent (A2A) integrations, or enterprise agent plugins for Global System Integrators (GSIs) or SaaS Independent Software Vendor (ISVs). * Experience leading cross-organizational technical programs with GSIs and translating repeatable field patterns into reusable partner code repositories and technical guides. * Experience defining technical strategy and influencing executive leaders within global partner organizations. * Expertise in Google Cloud's data analytics, database, and AI/ML platforms and services. * Proven track record of migrating and modernizing complex on-premises or multi-cloud data estates (e.g., Snowflake, Databricks, Teradata, Oracle) on Google Cloud and activating them for AI workloads. ## Description * Build reusable data-to-AI solutions, architectures, and accelerators with partners on Google Cloud. * Design and implement governed semantic layers and enterprise ontologies connecting BigQuery Graph, Conversational Analytics Agents, Looker, and Google Cloud Knowledge Catalog Custom Aspects to ground enterprise AI agents in verified business definitions. * Validate Gemini Enterprise plugins, remote Model Context Protocol. (MCP) servers, and reusable agent skills that integrate Google Data Cloud services with third-party enterprise systems. * Develop internal AI-assisted validation tools, evaluation rubrics, and automated architectural review workflows that scale Partner Engineering quality and turnaround velocity across partner engagements. * Lead technical onboarding for Data and AI launches, developing implementation guides, code assets, and enablement materials.