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# Capgemini Invent - Contextual Systems Engineer Consultant

- **Company:** Capgemini
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $72,000.0 - $136,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Systems Engineering, BigQuery, Data Architecture, Data Dictionary, Information Engineering, Graph Database, Neo4j, SQL Databases, Unstructured Data, Enterprise Data Management, Cloud Platform System, Snowflake, Data Layers, Video Streaming, Data Pipelines, Amazon Redshift
- **Published:** August 31, 2026
- **Apply:** https://dejobs.org/x/x/54448D53D3C34C27B34035BC6795055E/job/

## About the Role

* 3-5 years of experience in data engineering, analytics engineering, or data architecture
 * Hands-on experience with dbt , SQL , and at least one cloud data platform (e.g., BigQuery, Snowflake, Redshift)
 * Understanding of semantic modeling concepts such as dimensions, measures, metrics, and hierarchies
 * Strong documentation skills and attention to data quality

Beneficial experience:

 * Familiarity with graph database concepts (Neo4j preferred)
 * Exposure to knowledge and context platforms, vector databases, or streaming technologies
 * Interest in how AI systems consume enterprise data and knowledge at scale

## Description

As a Consultant, Contextual Systems , you will contribute to the design and delivery of AI-ready data and knowledge foundations that help enterprises bring business context to life. You will work within structured engagements, executing defined workstreams under senior guidance while quickly learning client environments and building domain and technical credibility.

In this role, you will help design and implement semantic layers, knowledge graphs, and context platforms that enable AI systems to understand enterprise data and processes more effectively. You will collaborate closely with senior consultants, architects, and client teams, contributing hands-on analytical and delivery output while developing your consulting skillset., * Building and configuring semantic layer components, including LookML models, dbt metrics, and dimension and measure definitions

 * Contributing to knowledge graph schema design and populating graph databases with domain-relevant data
 * Writing and testing data pipelines that feed context platforms with structured and unstructured data
 * Documenting semantic objects, context contracts, and data dictionaries for client use
 * Supporting discovery workshops focused on mapping enterprise data assets and knowledge flows
 * Assisting in the evaluation and configuration of knowledge and context platform tooling


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