Data & AI Architect: GenAI, Data Pipelines & Cloud Lead

Capgemini Engineering; Santa Clara (CA); Hybrid; USD 82,000 - 193,000; Full time

Benefits offered by this job

Paid time off

Medical insurance

401(k) plan

Life insurance

Employee assistance

Job summary

Capgemini Engineering is seeking a Data & AI Architect/Lead Engineer to drive end-to-end design and delivery of enterprise-scale Data and AI solutions in a hybrid Santa Clara, CA role. You will lead cross-functional teams, focusing on modern data platforms, GenAI/LLM applications, RAG frameworks, AI agents and intelligent automation.

The ideal candidate has 10+ years in data engineering, strong Python/SQL/ETL skills, Spark experience, and cloud proficiency (GCP preferred).

Qualifications

• 10+ years in Data Engineering or Data Platforms with leadership experience.
• Deep expertise in Python, SQL, ETL/ELT and distributed data processing.
• Experience with Spark and large-scale data architecture.
• Cloud experience across GCP, AWS or Azure; GCP preferred.

Responsibilities

• Lead end-to-end Data & AI solution design, architecture, development and delivery.
• Design scalable data models, data quality, data pipelines and analytics.
• Drive GenAI/LLM use cases, including RAG, AI agents and intelligent automation.
• Translate business problems into data products and roadmaps.
• Provide hands-on leadership across Python, SQL, APIs, ETL/ELT and cloud platforms.
• Establish best practices for data quality, governance, observability, security and performance.
• Lead architecture reviews and engineering standards; mentor teams.

Skills

Python

SQL

ETL/ELT

Spark

Cloud platforms

GenAI/LLM

RAG

AI agents

APIs

Data modeling

Tools

GCP

AWS

Azure

Vector databases

Job description

Capgemini Engineering is seeking a Data & AI Architect/Lead Engineer to drive end-to-end design and delivery of enterprise-scale Data and AI solutions in a hybrid Santa Clara, CA role. You will lead cross-functional teams, focusing on modern data platforms, GenAI/LLM applications, RAG frameworks, AI agents and intelligent automation.

The ideal candidate has 10+ years in data engineering, strong Python/SQL/ETL skills, Spark experience, and cloud proficiency (GCP preferred).