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Design and build agentic analytics systems using LLMs to automate insight generation and workflows. Requires five years coding Python and SQL, five years designing and deploying data pipelines with schema management, and five years in machine learning operations and data architecture. Build production-grade data systems, lead analytics infrastructure for Payments, and partner with Product, Data Science, and Engineering teams. Drive data quality, reliability, and governance standards across critical systems.

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Job Description

  • Design and build agentic analytics systems leveraging Large Language Models (LLMs) and AI to automate insight generation and workflows. Translate product needs into production-grade data systems (models, pipelines, and services).
  • Lead the design and coordination of analytics infrastructure powering product analytics across Payments.
  • Build AI-native analytics workflows, embedding intelligence directly into data and decision systems.
  • Partner with Product, Data Science, and Engineering to shape problem definitions and deliver the solutions.
  • Drive data quality, reliability, and governance standards across critical analytics systems. Build internal tools and frameworks to enable self-serve analytics and faster iteration for product teams.

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 5 years of experience coding in Python and SQL.
  • 5 years of experience designing and deploying data pipelines, including managing data schemas and processing data volume workflows.
  • 5 years of experience working with machine learning operations and data architecture design.

Preferred qualifications:

  • 5 years of experience designing enterprise-scale data platforms and analytics infrastructure.
  • 5 years of experience with AI/LLM-based systems, agentic workflows, or intelligent data applications.
  • 5 years of experience with using Gemini Command-line Interface, Cider Agents, LLM Extensions, Agent Development Kit (ADK) Agents etc.
  • 3 years of experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders or customers.
  • Experience with Machine Learning for production workflows.
  • Ability to operate across ambiguity and influence cross-functional technical decisions.
  • Bachelor's degree or equivalent practical experience.
  • 5 years of experience coding in Python and SQL.
  • 5 years of experience designing and deploying data pipelines, including managing data schemas and processing data volume workflows.
  • 5 years of experience working with machine learning operations and data architecture design.
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  • Role Senior Data Engineer, Product Analytics, Payments
  • Experience 5-7 years
  • Education Bachelor Degree, or equivalent experience
  • Work type On-site
  • Location Singapore
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Google
AI Research Lab · 500+ Members · Mountain View, CA, United States

Google builds internet, software, cloud, and AI products used by consumers, developers, and organizations. Its portfolio includes Search, YouTube, Android, Chrome, Maps, Gmail, Workspace, Google Cloud, advertising platforms, devices, and Gemini AI products. The company develops large-scale computing infrastructure and research that power information retrieval, communication, productivity, media, navigation, and machine learning. Google is the largest operating business within Alphabet and earns a substantial share of its revenue from digital advertising.

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Job Overview
Eligibility
Singapore Right to work in Singapore required.
Workplace
On-site
Job Posted:
1 week ago
Job Type
Full Time
Education
Bachelor Degree, or equivalent experience
Experience
5-7 years

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