Knowledge Graph Engineer

Career Guide

A Knowledge Graph Engineer builds and maintains systems that connect data into a structured network of entities and relationships. The goal is to make information easier to search, link, and use for applications like recommendations, semantic search, analytics, and AI assistants.

Browse All Roles

Key Responsibilities

Design the entity and relationship model for a knowledge graph
Define data standards and naming conventions for consistent meaning
Build data pipelines that transform source data into graph-ready formats
Implement graph storage solutions and optimize performance
Write and maintain graph queries for products and analytics
Create data quality checks for completeness, accuracy, and duplication
Manage entity resolution to merge records that refer to the same real-world thing
Partner with product and engineering teams to translate use cases into graph features
Document schemas, data sources, and governance rules
Monitor data freshness, reliability, and cost of graph operations

Top Skills for Success

Graph Data Modeling

Ontology Design

Entity Resolution

Data Engineering

Python

SQL

Graph Querying

RDF

SPARQL

Property Graph Modeling

Neo4j

Data Quality Management

API Design

Cloud Data Platforms

Stakeholder Communication

Career Progression

Can Lead To

Senior Knowledge Graph Engineer

Knowledge Graph Architect

Semantic Data Engineer

Data Platform Engineer

Machine Learning Engineer

Transition Opportunities

Staff Software Engineer

Data Engineering Manager

AI Platform Engineer

Data Architect

Search Relevance Engineer

Common Skill Gaps

Often Missing Skills

Ontology DesignGraph Data ModelingEntity ResolutionGraph QueryingData GovernanceGraph Performance TuningData Lineage

Development SuggestionsBuild a small portfolio project that ingests two to three real datasets, defines a clear schema, resolves duplicates, and exposes a few high-value queries through an API. Focus on measurable outcomes such as faster search, better matching, or improved data consistency.

Salary & Demand

Median Salary Range

Entry LevelUSD 100,000 to 135,000

Mid LevelUSD 135,000 to 180,000

Senior LevelUSD 180,000 to 240,000

Growth Trend

Growing. Demand is increasing as companies invest in AI search, personalization, and better data foundations, especially where data is spread across many systems.

Companies Hiring

Major Employers

GoogleMicrosoftAmazonAppleMetaIBMSalesforceServiceNowSnowflakePalantirBloombergThomson Reuters

Industry Sectors

TechnologySearch and AdvertisingEcommerceFinanceHealthcareInsuranceMediaTelecommunicationsManufacturingCybersecurity

Recommended Next Steps

Pick a graph approach and learn the core concepts of that ecosystem

Build a knowledge graph from public data and publish the schema and queries

Practice graph query writing using realistic product questions

Add entity resolution and data quality checks to your project

Deploy the graph on a cloud environment and document reliability basics

Create a short case study that explains the use case, design choices, and results

Tailor your resume to highlight graph modeling, pipelines, and business impact