Develop and maintain data models, pipelines, and ETL processes to ensure data quality, consistency, and accuracy

Keep the development of the data platform, including system architecture and efficient data products and pipelines within an agile working environment

Collaborate with cross-functional teams to identify and address complex data engineering challenges, developing robust solutions that meet business and user needs

Contribute to the development of data governance policies and procedures, ensuring compliance with relevant regulations and standards

Keep up-to-date with the latest data engineering technologies and trends, contributing to the continuous improvement of the data platform

A minimum of 3 years of experience in Data Software Engineering, demonstrating expertise in developing large-scale data products and pipelines

Proficiency in Python and PySpark, enabling you to develop efficient and scalable data processing solutions

In-depth knowledge of Databricks, Amazon Web Services and Microsoft Azure, showcasing your expertise in cloud-based data engineering technologies

Experience in developing and maintaining data models, pipelines, and ETL processes, demonstrating your comprehensive skill set

Strong focus on teamwork and exceptional interpersonal skills, allowing you to collaborate effectively with cross-functional teams

Fluent spoken and written English at an Upper-Intermediate level or higher

Hands-on experience in developing data products and pipelines using other programming languages, such as Java or Scala

Experience in deploying machine learning models in production environments and in implementing data security and privacy measures