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# Big Data Engineer Python

- **Company:** La Fosse Associates
- **Location:** Brussel, Belgium
- **Salary:** €130,000.0 - €156,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, Data Cleansing, Extract Transform Load (ETL), Data Systems, Data Warehousing, Apache Hadoop, Apache Hive, Python (Programming Language), Systems Integration, Workflow Management Systems, Data Processing, Cloud Platform System, Apache Spark, Containerization, Data Lakes, Kubernetes, Api Design, Data Pipelines, Docker
- **Published:** October 30, 2026
- **Apply:** https://www.adzuna.be/details/5946404054

## About the Role

* On-premises Data Lake technologies (Hadoop, Spark, Hive)

 * Large-scale data processing (Spark)

 * Orchestration tools (Apache Airflow)

 * Containerisation (Docker / Kubernetes)

 * Python programming

 * Architecture & Integrations:

 * API development

 * Cloud architectures (AWS, Azure)

Experience with real-time architectures and event streaming infrastructure is advantageous.

Behavioural Competencies

 * Collaboration: able to work closely and effectively with data scientists to translate complex analytical needs into functional technical solutions

 * Analytical & Organised: precise and methodical approach to data cleansing, preparation, integration, and pipeline design

 * Problem Solving: quick and efficient in addressing bottlenecks in data processing or orchestration errors

We require full-time availability (100%), although 80% availability will be considered.

## Description

This role focuses on developing, integrating, and optimising large-scale data flows. It involves close collaboration with data scientists to translate analytical models into practical technical solutions, requiring hands-on expertise in data cleansing, pipeline design, component orchestration, and modern data technologies such as Hadoop, Spark, and API development.

Mission & Responsibilities

 * Technical Collaboration: work closely with data scientists to develop effective technical solutions

 * Data Optimisation: perform data cleansing, preparation, and integration

 * Pipeline Engineering: design and build robust data pipelines

 * System Integration: manage component orchestration

 * Large-Scale Data Processing: responsible for batch Spark ETL, including data wrangling, joining, and aggregation

Technical Competencies

 * AI Ecosystems & Frameworks, including:

 * Modern Data Stack (MDS)