Data Engineering Intern

As a Data Engineering Intern at Qogita, your responsibilities will include collaborating with experienced data engineers to build and maintain our data platform. You'll work with various tools such as Airflow, Snowflake, and AWS, engaging in tasks that could range from data ops and engineering to analytics. Your role will involve implementing data pipelines, integrating with external APIs, and gaining hands-on experience in data management, all while supporting our broader engineering and data science teams.

To apply for the Data Engineering Internship at Qogita, you should be a Computer Science, Data Science, Engineering, or related subject student graduating in 2025. Familiarity with Python, SQL, and data pipelines is essential. Being an effective communicator and a fast learner who enjoys solving complex problems in a team environment is also crucial. If you're eager to learn and tackle challenges, you will fit right in with our team!

Yes, the Data Engineering Intern position at Qogita is a paid internship, with a gross monthly compensation of €800. This is a fantastic opportunity to gain valuable experience while receiving financial support during your internship period.

As a Data Engineering Intern at Qogita, you will engage in various projects that enhance our data platform. This could involve working on data pipeline implementations, optimizing data storage solutions using Snowflake and AWS services, or developing new integrations with external APIs. The projects vary based on your interests and strengths, ensuring that you are aligned with your career goals while contributing meaningfully to our team.

The Data Engineering Internship at Qogita offers a range of benefits that enhance your internship experience. You will receive 26 days of annual leave, access to a monthly wellness allowance, and a dedicated Learning & Development fund for your professional growth. Our flexible working environment allows for remote work, but you’ll also enjoy office socials and team-building events in our dog-friendly office in Amsterdam.

When answering this question, discuss specific projects or coursework where you've worked with data pipelines. Highlight the tools you’ve used, such as Airflow or similar technologies, and describe the challenges you faced and how you overcame them. This showcases your hands-on experience and problem-solving skills.

Be honest about your proficiency in languages such as Python and SQL, and cite specific projects where you've utilized them. Mention your eagerness to learn new languages or tools relevant to data engineering, as this aligns with Qogita's desire for ambitious learners and collaborative team players.

Talk about your learning strategies, such as online courses, documentation, or hands-on experimentation. Discuss how this proactive approach has helped you in previous projects, demonstrating your initiative and ability to adapt in a fast-paced environment like Qogita.

Provide a specific example detailing the problem, your thought process, and the solution you implemented. Highlight your analytical skills and teamwork, especially if you collaborated with others to achieve a solution, as this is crucial in a collaborative environment at Qogita.

Research Qogita's mission and products prior to the interview. Discuss how Qogita’s innovative use of technology to improve efficiencies in the B2B wholesale market excites you, and mention any specific aspects of their data-driven approach that resonate with your career goals.

Explain your method for prioritizing tasks, such as assessing deadlines, project complexity, or impact. Provide a past experience where your prioritization strategy was successful to illustrate your organizational skills and ability to handle multiple responsibilities at once.

Share any practical experience you have had with API integrations, describing specific projects where you utilized external APIs. Highlight your understanding of API functionalities and how you ensured smooth data flow in those projects to convey competence in a key skill for the internship.

Choose a team project that showcases your collaborative skills, describing your specific contributions, challenges faced, and the group's success. This will illustrate your ability to work effectively with others—an important quality at Qogita.

Discuss specific technologies mentioned in the job description, such as Airflow, Snowflake, and AWS. Express your enthusiasm for these tools and relate it to your experiences or coursework, reinforcing your commitment to contributing to Qogita's data platform.

Provide a clear and concise definition of data engineering, emphasizing the importance of data pipelines and data quality management. Share your passion for working with data and how you see it as essential to business strategy, reinforcing your interest in the Data Engineering Internship at Qogita.