Capgemini Invent - Contextual Systems Engineer Consultant

Capgemini • Chicago, NY

4d

About The Position

At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose. About the Job You’re Considering At Capgemini Invent, the Data Driven Transformation (DDT) team helps organizations unlock the full value of their data and AI investments to drive meaningful, scalable change. As part of Capgemini’s Strategy & Transformation Consulting practice, DDT partners with clients to shape data‑centric strategies, modern operating models, and AI‑enabled solutions that deliver measurable business outcomes. Our unified team model brings together expertise across Data & AI Advisory, Data Platforms & Architecture, and Applied Data Fusion , enabling seamless collaboration from strategy through execution. We work with leading organizations across industries including manufacturing, energy, consumer products, and life sciences to design future‑ready capabilities and accelerate value realization. The DDT team is recognized for: Enabling Generative AI to improve efficiency and unlock new sources of innovation Applying data and AI to sustainability and digital transformation initiatives Designing scalable, reusable data and AI products Delivering value quickly in complex, fast‑moving environments

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• 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

Benefits

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed