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Knowledge Context Engineer

Saicon Consultants Inc.

Bloomfield, New Jersey • Yesterday

Easy Apply

Contract, Third Party

Depends on Experience

Ontology Engineer – Knowledge Graph & Agentic AI (Neo4j / Graphwise)

Sradha Technologies LLC

Remote • 12d ago

Easy Apply

Contract

Depends on Experience

Analytics Engineer, Conversational Analytics

New York, New York • Today

Full-time

USD 137,300.00 - 166,000.00 per year

Knowledge Graph Engineer

Bank Of New York Mellon

New York, New York • Today

Full-time

Job Details

Skills

Summary

Key Responsibilities

Design, configure, and maintain catalog structures (entries, aspect types, tags, glossaries) 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 Qualifications

3 years of experience in data engineering, data governance, or metadata management.
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 Qualifications

Experience 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.
Prior consulting or client-facing experience.

Soft Skills

Strong 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.
Ingest metadata from knowledge sources.
Curation of Knowledge Assets – Business glossaries, tagging, aspect definition.
Build workflows to review and approve knowledge assets with key stakeholders.
Identify knowledge gaps and mitigation.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: saicon
Position Id: 26-90162
Posted 1 day ago

Fitment

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Job Details

Skills

Summary

Key Responsibilities

Design, configure, and maintain catalog structures (entries, aspect types, tags, glossaries) 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 Qualifications

3 years of experience in data engineering, data governance, or metadata management.
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 Qualifications

Experience 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.
Prior consulting or client-facing experience.

Soft Skills

Strong 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.
Ingest metadata from knowledge sources.
Curation of Knowledge Assets – Business glossaries, tagging, aspect definition.
Build workflows to review and approve knowledge assets with key stakeholders.
Identify knowledge gaps and mitigation.

Dice Id: saicon
Position Id: 26-90162
Posted 1 day ago

Fitment

Dice Job Match Score™

To see how well you match this job, please log in or create an account.

Once logged in, be sure to complete your profile to get the most accurate match score.

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

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