AI Data Engineer for Enterprise GenAI Pipelines

Capgemini; Kraków; On-site; PLN 180,000 - 240,000; Full time

Benefits offered by this job

Medicover healthcare

Private life insurance

Sports card

Capgemini Helpline

NEXT training platform access

Education platforms access

Job summary

Capgemini in Kraków seeks a Data Engineer blending data engineering with AI and agent-based systems. You will design and operate cloud-based data pipelines and platforms for analytics, enabling enterprise-grade AI solutions leveraging AI agents and large language models.

You will ingest and transform data, ensure quality and governance, and prepare datasets for AI workloads, collaborating with cross-functional teams to translate business requirements into scalable architectures.

Qualifications

• Strong experience in data engineering across enterprise data platforms.
• Proficient in Python and SQL for data processing and analytics.
• Experience designing and operating data pipelines.
• Familiarity with data modeling, data quality, and governance.
• Knowledge of retrieval-augmented generation (RAG) and AI agents.

Responsibilities

• Design, build, and operate cloud-based data pipelines.
• Ingest, transform, and manage structured and unstructured data.
• Prepare and expose data for AI workloads and feature datasets.
• Collaborate with AI teams to deploy data-driven AI solutions.
• Work with customers to translate data requirements into scalable architectures.

Skills

Data Engineering

Python

SQL

Data pipelines

Data governance

RAG

Agent concepts

LLMs / generative AI

Cloud platforms (AWS/Azure/GCP)

Job description

Capgemini in Kraków seeks a Data Engineer blending data engineering with AI and agent-based systems. You will design and operate cloud-based data pipelines and platforms for analytics, enabling enterprise-grade AI solutions leveraging AI agents and large language models.

You will ingest and transform data, ensure quality and governance, and prepare datasets for AI workloads, collaborating with cross-functional teams to translate business requirements into scalable architectures.