Google - Knowledge Catalog -Engineer

Google Knowledge Catalog EngineerChoosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
LocationsUSA
- LocalAbout the Job You're Considering:We are looking for a Google Knowledge Catalog Engineer to build, curate, and maintain an enterprise-wide data and context catalog on Google Cloud. This role owns the discoverability, quality, and semantic richness of data and AI assets — ensuring that technical metadata, business context, and lineage are accurate, enriched, and usable by both human analysts and AI/agentic systems (e.g., RAG pipelines, Gemini-based agents, BI.
Your Role and ResponsibilityDesign, configure, and maintain catalog structures (entries, aspect types, tags, glossaries) within Google Cloud's Knowledge Catalog (built on Dataplex) to organize data across BigQuery, Cloud Storage, Spanner, Vertex AI, Pub/Sub, and third-party sources.
Curate and enrich metadata — business definitions, ownership, sensitivity classifications, lineage, and usage context — so data assets are discoverable and trustworthy.
Build and maintain semantic layers, taxonomies, and ontologies that support natural-language search and AI grounding use cases.
Automate metadata ingestion and tagging pipelines (e.g., via Dataplex APIs, Cloud Functions, or Dataform) to keep the catalog continuously up to date.
Partner with data engineering, data governance, and business stakeholders to define and enforce cataloging standards, naming conventions, and data classification policies.
Support data quality and profiling initiatives, publishing scan results as catalog metadata.
Monitor catalog health, resolve metadata gaps or inconsistencies, and drive adoption across data and AI teams.
Contribute catalog context to downstream AI/agentic use cases (e.g., enabling Gemini or MCP-based agents to query curated metadata).
Document processes and provide training/enablement to data stewards and business users on catalog usage.
Required Qualifications5+ years of experience in data engineering, data governance, or metadata management.
Hands-on experience with Google Cloud Platform, including BigQuery and Google Cloud's Knowledge Catalog / Dataplex (or prior Data Catalog).
Strong SQL skills; working knowledge of Python for automation/scripting.
Familiarity with metadata management concepts: lineage, data classification, business glossaries, taxonomy/ontology design.
Understanding of data governance and compliance principles (access controls, sensitive data handling).
Experience with APIs and automation tooling for metadata ingestion.
Preferred QualificationsExperience with Gemini Ent. AI /Vertex AI, RAG architectures, or grounding AI agents in curated enterprise metadata.
Familiarity with Dataform, Cloud Composer/Airflow, or similar orchestration tools.
Exposure to data mesh or federated governance models.
Google Cloud certification (e.g., Professional Data Engineer, Professional Cloud Architect).
Prior consulting or client-facing experience.
Educations:Bachelor's degree in Computer Science, Information Technology, Data Science.
Soft SkillsStrong attention to detail and a structured, systematic approach to organizing information.
Ability to translate technical metadata into business-friendly context.
Collaborative mindset — comfortable working across data engineering, governance, and business teams.
Clear written and verbal communication for documentation and stakeholder enablement.
The base compensation range for this role in the posted location is: $101,180 to $182,624.
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time e