Capgemini Invent - Contextual Systems Engineer Senior Consultant

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

Your Role

As a Senior Consultant, Contextual Systems, you will own defined workstreams end‑to‑end within AI and data‑driven transformation engagements. You will design and implement the semantic and knowledge foundations that enable AI systems to understand enterprise context, working closely with senior architects and client data teams to deliver production‑quality solutions.

You will develop trusted relationships with day‑to‑day client counterparts, operate independently within your workstreams, and manage priorities while escalating appropriately. In addition to client delivery, you will begin contributing to internal knowledge development and practice assets within the Data Driven Transformation team.

Core responsibilities include:

• Designing and implementing semantic layer architectures end‑to‑end, including LookML models, dbt metrics, and ontologies
• Building knowledge graph schemas and implementing GraphRAG patterns for contextual AI retrieval
• Defining context contracts, including versioned semantic objects, governed datasets, and metric definitions
• Leading technical workshops to extract and encode enterprise knowledge into machine‑readable forms
• Evaluating and configuring knowledge platform tooling, including graph databases, vector stores, and embedding pipelines
• Partnering with AI engineering teams to integrate context layers into agentic and AI workflows

Your Skills + Experience

Required:

• 5–6 years of experience in data engineering, data architecture, or knowledge management
• Hands‑on expertise with semantic layer tooling such as LookML, dbt, or equivalent technologies
• Experience designing and working with knowledge graphs (Neo4j preferred)
• Familiarity with modern LLM integration patterns, including RAG, embedding pipelines, and vector stores
• Strong ability to translate business semantics into formal, well‑governed technical specifications

Beneficial experience:

• Experience working across cloud data platforms such as BigQuery or Snowflake
• Exposure to governance and catalog tooling (e.g., Collibra, Atlan)
• Interest in applied AI, agentic architectures, and enterprise‑scale contextual systems

The base compensation range for this role in the posted location is:  $105,600 - $199,480.

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 ro