Stage Data Engineer

Our Data Engineering team builds highly intuitive data solutions that underpin business functions across Sales, Marketing, Finance and Operations. We are looking for a Data Engineer Intern who are passionate about learning how to build structured, high-quality data pipelines. You will work closely with experienced data engineers, gaining exposure to Python, SQL, and Google Cloud Platform (GCP) tools such as BigQuery and managed Airflow, while learning how large-scale data systems operate in a modern digital environment. 

What you’ll do 

Support the development and maintenance of batch and real-time data processing pipelines using Python, SQL, and cloud technologies 
Collaborate with data engineers, data scientists, software engineers to understand data requirements and assist in delivering meaningful data solutions 
Participate in improving data quality by assisting with testing, validation, documentation, and basic performance checks 
Help conduct exploratory investigations and root-cause analyses on data issues under the guidance of senior team members 
Learn and apply software engineering best practices, including version control, code reviews, and continuous integration workflows 

Who you are 

You have a strong interest in software engineering and data technologies, and you are motivated to learn how modern data infrastructure is designed and operated 
You enjoy problem-solving, working with data, and collaborating with cross-functional teams 
You are curious, adaptable, and eager to learn new tools, frameworks, and engineering practices 
You value reliability, maintainability, and quality in your work 

Must have 

Currently pursuing or recently completed a BSc in Computer Science, Mathematics, Engineering, or a related quantitative field 
Foundational knowledge of Python and SQL (coursework or personal projects acceptable) 
Basic understanding of databases and data processing concepts 
Strong analytical and problem-solving skills 
Proficiency in English 

Nice to have 

Exposure to cloud platforms such as GCP, AWS, or Azure 
Experience with data processing frameworks (e.g., Apache Beam, Apache Spark) from coursework or personal experimentation 
Interest in large-scale data systems and modern pipeline architectures.