Staff Data Engineer, GenAI Applications, Global Business Consulting

Google•Apply•Published 5 days ago•First seen 5 days ago

In this role, you will need to have a strong background and passion for Generative AI to lead the architectural design, development, and operationalization of the end-to-end Generative AI solution. This full-stack solution will be built directly upon Google Play Partnerships' critical data assets and integrated into our core business consultation workflows.

This role offers a unique opportunity to work with mobile games and apps developers, translating complex data into innovative AI-driven products that directly enable the growth of their businesses.

Google Play offers music, movies, books, apps and games for devices, powered by the cloud. It syncs across devices and on the web. As part of the Android and Mobile team, Googlers working on Google Play do everything from engineering our backend systems, to shaping product strategy, to forming great content partnerships. They make it possible for people to do things like buy an ebook or song on their Android phone, then have it instantly available on their laptop. The Google Play team enhances the Android ecosystem by giving developers and partners a premium store where they can reach millions of users.

Responsibilities

Design, build and maintain scalable and secure data pipelines (ETL/ELT) required for GenAI and ML models, integrate and prepare large-scale, various datasets for model training and serving.
Lead the implementation of full-stack GenAI applications, and focus on robust data-centric techniques such as RAG and Fine-tuning.
Develop and maintain LLM-based agents, including configuring RAG workflows and utilizing advanced prompt engineering techniques like Multi-hop Chain of Thought Prompting (MCP).
Define and implement best practices for deploying, monitoring, and maintaining GenAI models and data systems in production environments, ensure performance, reliability, and scalability.
Serve as subject matter expert, partner with data scientists, stakeholders to translate complex, ambiguous business challenges into robust data modeling designs and production-ready solutions.

Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
7 years of experience troubleshooting technical issues for internal/external partners or customers.
Experience in either system design or reading code (e.g., Java, C++, Python).

Preferred qualifications:

10 years of experience writing and maintaining high-quality Extract, Transform, and Load (ETL) pipelines operating on a variety of structured and unstructured data sources.
Experience applying GenAI technologies to enterprise-scale products and solutions, particularly within a quantitative domain.
Understanding of MLOps/LLMOps practices for productionizing AI agents and models, and of cloud-native platforms (e.g., Google Cloud/GCP).
Ability to break down complex, ambiguous problems and propose impactful solutions through robust data modeling and system design.
Ability to communicate technical concepts to non-technical stakeholders, and attention to detail.
Excellent written, and verbal communication skills.