Data Engineer

ML6 (Headquarters: Amsterdam, Berlin, Ghent (EU))

Python SQL GCP AWS Azure Data Engineering Data Pipelines ETL ELT Data Warehouse Data Lake BigQuery Redshift Snowflake Spark Airflow Beam Cloud Infrastructure IaC Data Engineer

**Company:** ML6 is a Machine Learning consulting company building end-to-end ML solutions, keeping clients at the forefront of innovation using the latest AI research. We work with major clients across Europe on diverse, impactful projects, focusing heavily on robust data foundations.

**Role:** As a Data Engineer at ML6, you will be crucial in designing, building, and maintaining scalable and reliable data infrastructure that powers our clients' AI and ML initiatives. You will work extensively with cloud platforms and modern data technologies.

**Responsibilities:**
- Design, build, and optimize data pipelines for ETL/ELT processes.
- Develop and manage data lakes, data warehouses, and databases on cloud platforms (GCP, AWS, Azure).
- Ensure data quality, reliability, and accessibility for ML models and analytics.
- Implement infrastructure as code (IaC) practices.
- Collaborate with ML Engineers and Data Scientists to understand data requirements.
- Monitor and troubleshoot data infrastructure performance.
- Stay current with best practices in data engineering and cloud technologies.

**Technical Skills:**
- Strong proficiency in Python and SQL.
- Experience building data pipelines using tools like Apache Airflow, Apache Beam, Spark, or cloud-native services (e.g., Dataflow, Glue, Data Factory).
- Expertise in cloud data warehousing (BigQuery, Redshift, Snowflake) and data lake technologies.
- Hands-on experience with major cloud providers (GCP, AWS, Azure).
- Knowledge of data modeling, database design, and data governance principles.
- Familiarity with containerization (Docker) and orchestration (Kubernetes) is a plus.

**Ideal Candidate:** A skilled Data Engineer passionate about building robust, scalable data solutions in the cloud. You excel at designing data architectures, building efficient pipelines, and ensuring data quality. You enjoy working collaboratively to enable data-driven decision-making and cutting-edge AI applications.