G

Google

Runs Search and YouTube and builds Gemini AI

Agentic Data Cloud Architect - Google Cloud

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeSingaporeNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree or equivalent practical experience.
  • 10 years of experience delivering data and analytics solutions in a customer-facing or support role.
  • Experience building and deploying enterprise generative AI applications and agentic workflows integrated with modern data platforms.
  • Experience architecting distributed data systems, including Lakehouse and Data Mesh; batch and streaming pipelines, including Spark, Flink, BigQuery, and Iceberg; and transactional databases, including PostgreSQL, MySQL, and NoSQL databases.
  • Experience in cloud-native data warehousing, ETL/ELT pipelines, real-time event streaming, governance, and end-to-end migrations.
  • Experience partnering with, influencing, and presenting architectures to executive leaders and technical stakeholders.

Responsibilities

  • Serve as the primary technical partner to customer CTOs and chief architects, leading high-stakes workshops to align their technology roadmaps with Google’s Data and AI strategy.
  • Act as principal architect for Google’s Agentic Data Cloud, set engineering standards, win complex workloads, and accelerate adoption across lighthouse engagements from evaluation through ramp.
  • Capture repeatable patterns to build scalable Golden Path blueprints, reference architectures, and field-ready assets that drive broad adoption across thousands of customers.
  • Synthesize customer friction points and cross-product gaps into authoritative engineering requirements to shape and protect Google’s unified Data and AI narrative.
  • Mentor and guide subregional Datacloud Customer Engineers, remain engaged for critical architectures, and direct the team to deliver secure, scalable solutions.

Desired Qualifications

  • Experience interacting with C-level executives, such as CTOs, Chief Data Officers, and Chief Information Officers, to translate complex business requirements into technical strategies through clear, compelling narratives; organizational, communication, and leadership skills; and the ability to prioritize and manage multiple time-sensitive initiatives.
  • Knowledge of emerging agentic technologies and their implications for data architecture.
  • Proficiency writing, refactoring, and debugging Python, PySpark, and SQL natively to support high-performance data engineering, machine-learning frameworks such as PyTorch and TensorFlow, and workload troubleshooting.
  • Technical expertise designing distributed systems, data platforms, and AI/ML architectures for enterprise scale.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size
10,001+
Company stage
IPO
Headquarters
Mountain View, CA
Founded
1998

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