AI & Data Engineer: Build Scalable Data Pipelines & ML

3707 A.F.D. Belgium srl Company; Sint-Jans-Molenbeek; Hybrid; EUR 80,000 - 120,000; Full time

Benefits offered by this job

Hybrid work

Flexible client-site work

Job summary

Accenture AFD.Tech in Brussels is seeking a versatile Data Engineer / AI Engineer to design and maintain modern data platforms and contribute to AI/ML initiatives. You will work across client environments, collaborating with data scientists, analysts and software engineers to deliver scalable data pipelines and AI solutions.

The role emphasizes Python/SQL, cloud data ecosystems and deployment of ML models, with a hybrid work arrangement and strong collaboration across multidisciplinary teams.

Qualifications

• 3+ years of experience in Data Engineering or AI/ML roles.
• Strong Python and SQL skills with production data pipelines.
• Experience with cloud-based data platforms and modern data ecosystems.

Responsibilities

• Design, build and maintain scalable data pipelines and ETL/ELT processes.
• Collect, transform and integrate data from structured and unstructured sources.
• Develop data models and architectures to support analytics and AI use cases.
• Collaborate with data scientists and analysts to provide accessible datasets.
• Contribute to ML/AI solutions and ML model deployment.
• Implement monitoring and continuous improvement for data solutions.

Skills

Python

SQL

Data pipelines

ETL/ELT

Cloud platforms

AI/ML fundamentals

REST APIs

Git / CI/CD

Docker / Kubernetes

Generative AI basics

Tools

Databricks

Apache Spark

Azure Data Factory

Snowflake

Kafka

Airflow

dbt Cloud

Job description

Accenture AFD.Tech in Brussels is seeking a versatile Data Engineer / AI Engineer to design and maintain modern data platforms and contribute to AI/ML initiatives. You will work across client environments, collaborating with data scientists, analysts and software engineers to deliver scalable data pipelines and AI solutions.

The role emphasizes Python/SQL, cloud data ecosystems and deployment of ML models, with a hybrid work arrangement and strong collaboration across multidisciplinary teams.