Senior Data Engineer, Remote

As a Senior Data Engineer at Experian, you will be responsible for solving complex technical challenges, contributing to the architecture and design of our EMS systems, mentoring junior engineers, and leading technical projects. You will work hands-on with technologies like Scala and deal with data at an unprecedented scale, ensuring that our products are efficient and effective.

To qualify for the Senior Data Engineer role at Experian, candidates typically need 5+ years of experience in software engineering, strong familiarity with Scala or Java, and experience with high-scale systems. Additional expertise in data ingestion, ETL processes, and machine learning techniques will also be beneficial.

Yes, the Senior Data Engineer position at Experian is fully remote, allowing you to work from anywhere in the United States while accommodating Eastern Time Zone work hours. This flexible setup supports a work-life balance that we value at Experian.

In the Senior Data Engineer role at Experian, you will primarily use technologies like Scala, Google Cloud Platform, Airflow, Kubernetes, and data processing tools such as Spark and BigQuery. Familiarity with machine learning frameworks and Python is also advantageous.

At Experian, development and collaboration are at the heart of our culture. As a Senior Data Engineer, you’ll have opportunities to mentor junior engineers and lead technical projects, fostering a culture of continuous learning and improvement. We celebrate individual contributions and emphasize teamwork.

Experian offers a competitive benefits package for the Senior Data Engineer position, including medical, dental, and vision coverage, a matching 401K plan, flexible work options, and generous paid time off, including volunteer time. We believe in rewarding our excellent employees.

Experian is recognized as a Great Place To Work™ in numerous countries, emphasizing a people-first approach. We focus on DEI, work-life balance, and employee wellness, aiming to create an engaging environment for all employees, including those in the Senior Data Engineer role.

In answering this question, share specific projects where you utilized Scala for data engineering tasks. Detail how you implemented algorithms or processed large datasets and mention any challenges faced and overcome.

When discussing ETL processes, outline the steps you take from extraction to loading. Emphasize efficiency, data quality, and scalability—mentioning tools like Airflow or Spark can highlight your technical knowledge.

Talk about your approach to mentorship, including how you provide guidance, support learning, and facilitate your mentees' growth. You may share specific examples of how you've helped others succeed in their careers.

Illustrate your familiarity with real-time data processing. Provide an example of a project where real-time data was crucial and explain the technologies you used, the challenges you faced, and how you solved them.

Explain the measures you take during data handling to maintain privacy and security, such as data encryption, access controls, and compliance with regulations. Show your understanding of industry standards.

Describe your experience collaborating with other departments, such as product management or data science, and highlight how you streamline communication and ensure alignment with project goals.

Select a project that showcases your leadership skills and technical expertise. Discuss the project's goals, your role in managing the team, and how you led it to successful completion.

Share your technical toolkit, highlighting specific experiences with tools like Google Cloud, Spark, or Kubernetes. Be prepared to discuss how these tools have helped you in data engineering tasks.

Outline your systematic approach to debugging, emphasizing analytical thinking and troubleshooting steps. Mention specific tools or methods you use to identify and resolve issues.

Discuss trends like the rise of machine learning, cloud data platforms, or data governance. Show how you keep abreast of these changes and apply them to your work as a Senior Data Engineer.