AI & Data Engineer: From Presales to Production

NTT DATA, Inc.; Machelen; Hybrid; EUR 85,000 - 130,000; Full time

Benefits offered by this job

Annual bonus

Lunch vouchers

Company car or Mobility budget

Hospitalisation insurance

Group and disability insurance

Lease bike option

31 days of holiday + seniority days

Data and voice subscription

Job summary

NTT DATA, Inc. is seeking an AI & Data Engineer to work with clients on AI and data transformation projects. You will blend presales activities, solution design, and hands-on engineering to deliver production-ready data platforms and AI solutions.

You will engage directly with clients across the full lifecycle from PoVs to deployment and handover. The role emphasizes enterprise data foundations, data lakes, data warehouses, data pipelines, and integrating AI with business processes.

Qualifications

• Degree or equivalent professional experience in a relevant field.

Responsibilities

• Understand customer requirements from technical and functional perspectives.
• Assess customer data landscapes and identify AI/data use cases.
• Participate in presales activities and customer workshops.
• Design data and AI architectures and implement data platforms and pipelines.
• Containerize and deploy solutions in cloud and container platforms.
• Write implementation plans and technical documentation and support handover.

Skills

Presales involvement

Design

Hands-on engineering

AI & Data engineering

Data Lakes/Lakehouses

SQL

Python

ETL/ELT

Data modeling

Cloud platforms

Docker

Kubernetes

CI/CD

MLOps/DataOps

Education

Degree in Computer Science, Engineering, AI, Data Science or equivalent

Tools

Docker

Kubernetes

Azure Data Factory

Azure Databricks

SQL/NoSQL

Python

REST APIs

Job description

NTT DATA, Inc. is seeking an AI & Data Engineer to work with clients on AI and data transformation projects. You will blend presales activities, solution design, and hands-on engineering to deliver production-ready data platforms and AI solutions.

You will engage directly with clients across the full lifecycle from PoVs to deployment and handover. The role emphasizes enterprise data foundations, data lakes, data warehouses, data pipelines, and integrating AI with business processes.