Akkodis is seeking a skilled Data Engineer to join its innovative and technology-driven teams.

The Data Engineer plays a key role in designing, building, and maintaining scalable and reliable data platforms that enable data-driven decision-making across business, R&D, and digital products.

The position focuses on data ingestion, transformation, storage, and secure access to data within modern cloud-based architectures, working closely with stakeholders, architects, analysts, and developers.

Role :

Understand business, R&D, and technical requirements related to data usage

Design, build, and maintain robust and scalable data pipelines (batch and streaming)

Extract raw data from multiple sources such as APIs, databases, files, IoT systems, and third-party platforms

Transform, clean, enrich, and standardize data according to a centralized data model

Develop and maintain backend services and REST APIs to expose data to web applications, BI tools, and analytics platforms

Manage data storage within data lake, lakehouse, and data warehouse architectures

Implement access control, security, and data governance policies across the data platform

Ensure data quality, reliability, observability, and performance of data pipelines

Optimize SQL queries and data processing workloads

Support reporting, dashboards, and advanced analytics use cases

Collaborate with data scientists, analysts, architects, product owners, and project managers

Contribute to data engineering standards, best practices, and architectural guidelines

Support end-to-end delivery from requirement analysis to production deployment

Your profile :

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field

Minimum 3 years of experience as a Data Engineer (medior/senior profiles preferred)

Experience in R&D, innovation, or technology-driven environments is a plus

Strong proficiency in English (written and spoken)

Knowledge of French and/or Dutch is an asset

Strong interest in modern data technologies and continuous improvement

Data Engineering and data pipeline development (ETL / ELT)

Strong SQL skills and experience with relational and analytical databases

Programming languages: Python (mandatory), knowledge of Scala or Java is a plus

Big Data and processing frameworks: Spark, Databricks or equivalent

Workflow orchestration tools: Airflow, Azure Data Factory, or similar

Cloud platforms: Azure (preferred), AWS or GCP

Data storage architectures: Data Lake, Lakehouse, Data Warehouse

REST API development and integration

Containerization and deployment: Docker, Kubernetes

BI and visualization tools: Power BI, Tableau or similar

Understanding of data modeling, data governance, and security principles