Data Engineer

As a Data Engineer at our partner company, your main responsibilities will include designing and managing scalable data architectures for LLM use cases, building and maintaining robust data pipelines from diverse sources to a vector database hosted on AWS, and implementing role-based access controls and data masking protocols. You'll also optimize processes via monitoring tools and collaborate in Agile teams to achieve project goals.

To be a successful Data Engineer at our partner company, you should have expertise in SQL and Python, as well as proficiency in working with both structured and unstructured databases. Experience with vector databases and data orchestration tools is essential, along with a solid understanding of Agile/Scrum methodologies. Strong English communication skills are important, and familiarity with AWS services and the real estate sector would be a plus!

The work culture for Data Engineers at our partner company promotes collaboration and innovation. You will be joining an Agile team that values self-motivation and curiosity, providing an environment where you can thrive. The company encourages learning and professional growth, offering a generous annual training budget to further enhance your skills.

Yes, as a Data Engineer at our partner company, you will be working with various data orchestration tools, AWS for cloud services, and vector databases. You will also use monitoring tools to create dashboards and logging systems for tracking the performance of data pipelines and processing flows.

The benefits for Data Engineers at our partner company include a 13th-month bonus, 37 vacation days per year, a premium pension scheme with minimal employee contribution, and a flexible working policy with support for home-office setups. Additionally, the company provides a €1,500 annual training budget and commuting support options.

In answering this question, be sure to highlight specific projects where you designed and implemented data pipelines. Discuss the methodologies you used, the tools applied, and how you ensured data integrity and security throughout the process.

To effectively answer this question, demonstrate your knowledge of role-based access control by explaining how it regulates user access based on their roles. Include an example from your past work where you implemented or managed such access controls.

Focus on specific techniques you use to optimize data processing in cloud platforms like AWS. Discuss strategies such as efficient resource allocation, automated scaling, or cost management approaches, and provide examples of when you applied these strategies.

Here, discuss your familiarity with Agile principles by sharing how you've worked in Agile teams. Explain the benefits you've observed and give examples of how Agile practices have improved product development and delivery in your previous projects.

Mention languages like SQL and Python as essential for data engineering tasks. Additionally, refer to relevant tools such as ETL frameworks, data orchestration tools, and any libraries or frameworks that enhance your workflow. Examples from past experiences would provide great context.

Discuss your strategies for monitoring and logging processes, mentioning any specific tools you use. Explain how effective logging can aid in troubleshooting and performance optimization, and share an example of how monitoring significantly improved system reliability in a project.

Here, explain your understanding of vector databases, their importance in data engineering, and any practical experience you have had with them. Provide examples of projects where you've utilized vector databases to enhance data retrieval processes.

Share a specific challenge you faced in a previous role regarding data architecture, detailing the problem and the steps you took to overcome it. Discuss the tools and methodologies you used and the impact of your solution on the project.

In your response, outline methods you employ to maintain high data quality and integrity, such as data validation checks and data cleaning processes. Using concrete examples of how you've implemented these practices will provide credibility to your answer.

This is your chance to express enthusiasm for the role and the company. Discuss what attracts you to their mission, mentioning any specific projects or advancements. Personalize your answer to reflect genuine interest and alignment with their values and goals.