Data Engineers - job 2 of 17

Data Engineers at American Express are tasked with collaborating with product teams to define data requirements, map out data architectures, and ensure seamless data integration into existing systems. This includes documenting data needs, maintaining data models, and continually optimizing database performance based on business goals and industry advancements.

To qualify for the Data Engineer position at American Express, candidates must hold a Master’s degree in Computer Science, Engineering, Information Systems, or a relevant STEM field. Additionally, they should have two years of relevant database administration experience, plus demonstrated skills in managing Cassandra and Couchbase environments, among other technologies.

American Express is committed to career growth for its Data Engineers. The company offers comprehensive training programs, mentorship opportunities, and access to resources that enhance professional development. This ensures that data engineers stay current with emerging technologies and best practices in database management.

Yes! American Express offers flexible telecommuting options for its Data Engineers, allowing them to work from anywhere within the U.S. This flexibility helps promote a healthy work-life balance, catering to the diverse needs of our employees.

Data Engineers at American Express enjoy a rich benefits package that includes competitive base salaries, bonus incentives, a comprehensive medical benefits plan, 20+ weeks of paid parental leave, and free access to wellness centers. The company also provides retirement savings plans with a matching contribution, along with free financial coaching, ensuring holistic support for all employees.

In answering this question, highlight specific database technologies you've worked with, detailing your responsibilities in maintenance and optimization. Discuss any notable projects or challenges you've overcome to demonstrate your expertise and relevance to the Data Engineer position.

To answer effectively, describe your method for gathering input from stakeholders, how you synthesize that information, and the tools you use for documentation. Mention the importance of clear communication with team members and stakeholders throughout the process.

Explain the strategies you use for testing and validating new architectures. Discuss your approach to monitoring performance post-integration and how you address any integration issues to maintain system integrity.

Highlight your specific experiences with NoSQL technologies, such as Cassandra or Couchbase, while discussing the advantages and use cases for both NoSQL and traditional databases. Emphasize your ability to choose the right technology based on project requirements.

Prepare a structured response, detailing the challenge, your thought process in diagnosing it, and the steps you took to resolve it. Also, outline the impact of your solution on the project or business outcomes.

Discuss specific tools like Nagios Core or Icinga, explaining how you implemented and utilized them for monitoring database health and performance. Give examples of metrics you focus on and how you respond to alerts.

Provide examples of automation scripts you’ve developed, the tasks you've automated, and how it improved efficiency. Discuss your approach to maintaining these automation routines for ongoing reliability.

Share your process for UAT, highlighting how you engage stakeholders, set criteria for acceptance, and handle feedback. Emphasize the importance of thorough testing and communication in achieving successful outcomes.

Discuss programming languages relevant to the position, like Python or Java. Explain how you apply these languages in database management, data processing, or automation tasks, providing concrete examples.

Identify a current trend such as cloud database solutions or machine learning integration in data management. Explain why you find it significant and how it influences your work as a Data Engineer.