(846) Senior Data Engineer

As a Senior Data Engineer at Nearsure, your key responsibilities include enhancing and optimizing data pipeline architecture, designing and implementing data integrations, and ensuring secure data flow for multiple projects. You will collaborate closely with other data professionals, identify and resolve data quality issues, and support system design, ensuring robust data security and compliance with best practices.

To apply for the Senior Data Engineer role at Nearsure, you should have a Bachelor's Degree in Computer Science, Engineering, or a related field, along with at least 5 years of experience working as a Data Engineer. Proficiency in Python, knowledge of data modeling for data warehouses, and experience with cloud platforms like Azure are essential requirements. Additionally, advanced English skills are required for effective client communication.

Nearsure offers an attractive benefits package for Senior Data Engineers, including 100% remote work options, paid time off according to your country's laws, a day off during your birthday week, and annual refundable credits for personal perks. We prioritize work-life balance and provide a dedicated People Care team to support your needs from day one.

The hiring process for the Senior Data Engineer position at Nearsure begins with an initial discussion about your experiences with our recruiters, followed by a technical interview with our developers to evaluate your skills. If you succeed, you’ll have the opportunity to meet our clients and learn more about the projects you'll contribute to.

As a Senior Data Engineer at Nearsure, you'll engage in intricate data projects focused on enhancing data architectures and streamlining data flows. Your role involves collaborating with cross-functional teams to design secure data pipelines, ensuring that data meets quality standards and provides actionable insights for business users.

When answering this question, highlight specific projects where you implemented CI/CD techniques for data pipelines. Discuss the tools you used, challenges faced, and how you ensured data quality and efficiency. This shows your hands-on experience and problem-solving skills.

Discuss your understanding of data security measures, such as encryption, access controls, and authentication methods. Provide examples of how you've implemented these practices in past roles to protect sensitive information, ensuring that you demonstrate both technical knowledge and an emphasis on data integrity.

Be honest in your response, discussing your preferences for tools like Python, SQL, or specific data warehouse technologies. Explain how they enhance your workflow and contribute to data accuracy and efficiency, and be prepared to discuss your decision-making process in choosing these tools.

Share a specific situation where you faced complex data migration issues. Detail how you approached the problem, the methodologies utilized, and the successful outcome. This showcases your critical thinking and adaptability in dealing with potential project hurdles.

Describe your process for assessing and validating data quality. Highlight tools or methodologies you employ for data consistency and accuracy, such as automated testing or monitoring solutions, demonstrating your commitment to delivering high-quality data solutions.

Detail your hands-on experience with Azure and any related services like Azure Data Factory or Synapse Analytics. Provide examples of projects where you've utilized these platforms and how they improved data handling and processing efficiency.

Highlight your ability to simplify complex technical concepts for a non-technical audience. Provide an example of how you have effectively communicated data insights in a way that aligns with business objectives or project goals, showcasing your strong communication skills.

Talk about specific instances where you've integrated APIs for data collection or delivery. Mention the types of APIs you've worked with (e.g., REST, SOAP) and the impact of these integrations on overall project success.

Share your strategies for staying updated, whether through online courses, reading industry blogs, attending webinars, or engaging with professional communities. This conveys your dedication to personal and professional growth and your commitment to applying best practices.

Discuss current industry trends such as data privacy concerns, managing large datasets, or the challenges of integrating disparate data sources. This shows your awareness of broader industry issues and positions you as a knowledgeable candidate who can contribute valuable insights.