Engineering Director, Knowledge Catalog
Google · Bengaluru, Karnataka, India
- On site
- Full-time
- $250,000 / year
- Bengaluru, Karnataka, India
Job highlights
- Lead AI-first data fabric strategy.
- Define GenAI and data governance evolution.
- Collaborate with C-level leaders.
- Influence Google's AI data strategy.
- Drive autonomous data ecosystem development.
About the role
About The Job
Within Google Cloud, Dataplex is the intelligent data fabric that enables organizations to unify, manage, and govern their data across lakes, warehouses, and data marts. Our mission is to transform data management from a manual, siloed process into a seamless, autonomous, and secure ecosystem that scales with the speed of modern business. This is being done by deeply infusing Generative AI into the Dataplex platform. This role is central to that mission, defining how we leverage Dataplex’s unique ability to automate data profiling, quality, and lineage to provide a trusted, self-healing, and AI-ready foundation for the entire data lifecycle.
As an Engineering Director, you will be an expert visionary and generalist, leading the technical and architectural reinvention of the Dataplex platform. You will define and drive the long-term strategic technical priorities for integrating AI as a core competency into our data governance and integration fabric.
In this role, you will be responsible for defining how Generative AI, automated metadata management, and our distributed data mesh architecture will evolve to create a truly autonomous, trusted, and AI-ready data ecosystem. You will employ a hybrid approach of direct technical guidance, mentorship, and risk/growth management. You will act as an escalation point for technical decisions across the team and function as a trusted partner for other C-level leaders in defining strategy and shaping our investment portfolio. Additionally, you will function as a trusted partner and key technical influencer both internally and externally.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
- Work closely with our strategic customers to understand their complex data silos and co-develop our AI-first data management roadmap.
- Partner with C-level leaders to define the strategy for the next generation of data fabrics, ensuring Dataplex is the backbone of Google Cloud’s data strategy.
- Build Product and UX relationships. Collaborate with SRE and Privacy, Security, and Compliance teams.
- Influence thought leaders across Google Cloud (e.g., Vertex AI, BigQuery) and Google (e.g. DeepMind) to align roadmaps, ensuring that the data fueling Google’s AI models is governed, high-quality, and seamlessly accessible.
- Lead Dataplex’s AI-first long-term strategy, defining roadmaps for autonomous governance, AI metadata discovery, and self-healing pipelines while maintaining technical excellence.
- Manage complex tradeoffs such as LLM integration (i.e. rewrite vs. encapsulate), balancing AI automation with manual controls, and transitioning between centralized and data mesh architectures.
Key skills/competency
- Engineering Director
- Knowledge Catalog
- Google Cloud
- Dataplex
- Generative AI
- LLMs
- Data Governance
- Data Management
- Cloud-native data platforms
- Distributed data processing
Skills & topics
- Engineering Director
- Knowledge Catalog
- Google Cloud
- Dataplex
- Generative AI
- LLMs
- Data Governance
- Data Management
- Cloud Engineering
- AI/ML Leadership
How to get hired
- Tailor your resume: Highlight experience with AI/ML, LLMs, and cloud-native data platforms relevant to Google Cloud's Dataplex.
- Showcase leadership: Emphasize your 10+ years of experience leading engineering organizations and your strategic vision.
- Demonstrate technical depth: Detail your expertise in distributed data processing frameworks and AI-driven data management.
- Understand Google's culture: Research Google Cloud's mission, values, and the innovative work within Dataplex.
- Prepare for technical and leadership discussions: Be ready to discuss complex architectural decisions and strategic roadmaps.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key AI/ML technologies for the Engineering Director, Knowledge Catalog role at Google Cloud?
- For the Engineering Director, Knowledge Catalog position at Google Cloud, key AI/ML technologies include expertise in Generative AI, Large Language Models (LLMs), and vector embeddings. This role also involves leveraging these technologies for data classification, sensitive data detection, and discovery within multi-cloud environments.
- What is the primary goal of the Dataplex platform at Google Cloud?
- The primary goal of the Dataplex platform at Google Cloud is to serve as an intelligent data fabric that enables organizations to unify, manage, and govern their data across lakes, warehouses, and data marts. Its mission is to transform data management into a seamless, autonomous, and secure ecosystem, deeply infused with Generative AI.
- What kind of experience is required for the Engineering Director role at Google?
- The Engineering Director role at Google requires a Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. It mandates 15 years of experience in software engineering and 10 years of experience leading engineering organizations.
- How does this role at Google Cloud influence Google's broader AI strategy?
- This role is central to Google Cloud's AI strategy by defining how the Dataplex platform's capabilities in data profiling, quality, and lineage will provide a trusted, AI-ready foundation. The director will influence thought leaders across Google Cloud and Google (e.g., Vertex AI, BigQuery, DeepMind) to ensure that data fueling Google's AI models is governed, high-quality, and accessible.
- What are the preferred qualifications for an Engineering Director at Google Cloud focused on Knowledge Catalog?
- Preferred qualifications include expertise in AI/ML (LLMs, vector embeddings), architectural proficiency in cloud-native data platforms with a focus on modernization, and deep experience with distributed data processing frameworks like Spark, Flink, and BigQuery.
- What is the work arrangement for the Engineering Director, Knowledge Catalog position?
- This position offers flexible working locations in Hyderabad, Telangana, India, or Bengaluru, Karnataka, India. Given the director-level and global nature of Google Cloud, it's likely a hybrid or on-site arrangement within these specified office locations.