Data Engineer

To qualify for the Data Engineer position at Surfshark, candidates should have a minimum of 2 years of proven experience in Data Engineering or related fields. Proficiency with cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure is essential, alongside advanced programming skills in Python or related languages. Experience with data orchestrators like Apache Airflow, as well as IoC tools for infrastructure management, is also required.

As a Data Engineer at Surfshark, your responsibilities will include designing, building, and maintaining robust cloud infrastructure for data engineering processes, optimizing data pipelines, and ensuring that the code adheres to established best practices. You'll work closely with cross-functional teams to identify and implement data solutions that address business needs, ensuring the quality and reliability of data across the organization.

Surfshark is committed to the growth and learning of its Data Engineers by providing dedicated time for learning, access to conferences, and various online learning platforms. Employees are encouraged to engage with books and resources that enhance their professional skills, ensuring they stay at the forefront of data engineering advancements.

A Data Engineer at Surfshark will utilize a variety of tools and technologies, particularly cloud platforms like AWS or Google Cloud, and programming languages like Python. Experience with data orchestrators such as Apache Airflow and tools for infrastructure provisioning like Terraform or Ansible will also be vital for the role.

Working as a Data Engineer at Surfshark comes with numerous benefits, including opportunities for professional development, health and wellness programs, a flexible work-from-anywhere policy, additional vacation days based on tenure, and premium Surfshark accounts for you and your family. The company also fosters a sense of community with traditions like team-building events and celebrations.

When answering this question, focus on specific cloud platforms you've worked with, detailing your experience in using them for data storage, processing, and analytics. Highlight any projects where you've integrated data from different sources or designed data pipelines using these platforms.

Discuss your approach to data pipeline optimization, including techniques you've employed to enhance performance, scalability, and reliability. Mention any tools you use, like Apache Airflow, and describe a particular scenario where your optimizations led to measurable results.

Emphasize the data validation and testing methodologies you adhere to while building data pipelines. Talk about the importance of using automated testing and monitoring tools to ensure data integrity and quality before it is utilized by other teams.

Share a project where you faced significant challenges, explaining the context, the obstacles, and how you approached solving those issues. Highlight any collaborations with other teams and the outcomes achieved.

Mention the resources you utilize to keep up with the latest trends and advancements in data engineering, such as online courses, webinars, blogs, and professional communities. Highlight how you apply this learning to your work at Surfshark.

Discuss the importance of collaboration with other teams, such as analytics and data platform engineers. Highlight how sharing insights, challenges, and solutions leads to improved data solutions that align with business objectives.

Talk about specific data orchestrators you've worked with, explaining how you've employed them to automate and streamline workflows. Provide examples of projects where orchestration significantly improved efficiency.

Focus on the practices you implement to ensure data security and compliance with regulations. Discuss any experiences where you had to navigate complex compliance requirements, and how you incorporate security best practices into your projects.

Mention your preferred programming languages for data engineering, such as Python, and explain why you favor them. Discuss how their libraries and frameworks have contributed to your effectiveness in building data solutions.

Illustrate your professional aspirations, expressing a genuine desire for growth and leadership opportunities within data engineering. Talk about the specific skills or experiences you aim to acquire and how you see them impacting your future at Surfshark.