Customer Support Engineer

Customer Support Engineer, Data Platform

Location:

San Francisco CA, New York NY, or Remote

Team:
Customer Success, Data Exchange Platforms

Job Description

At Capital One, we’re building a leading information-based technology company. We think big and do big things. We were the first company to develop and offer mass customization and personalization of credit card products, and we have been innovating relentlessly ever since. Today we are a high-tech company, a scientific laboratory, and a nationally recognized brand all in one that reaches tens of millions of consumers.

We are a passionate and entrepreneurial team that embraces bold ideas, fosters collaboration and delivers great experiences for our customers.

Are you inspired by big data and the endless possibilities it creates? At Capital One, we are harnessing big data to improve everyday experiences for our millions of customers across banking, credit cards, investments and car loans. As our customers go about their daily lives, they generate a river of data. It flows 24-hours a day, touches all lines of business and represents a tremendous opportunity for Capital One.

By making this data available, we enable anyone at Capital One to access the data for business analysis and innovation.

We are seeking a customer-centric, energetic, and highly-motivated individual to join our Customer Support Team as a Customer Support Engineer (CSE). The Customer Support team provides an effective model for supporting and maintaining relationships with Capital One lines of business as they use our massive and complex data ecosystem. System users will look to you for technical guidance and for advice in addressing their product usage and issue needs.

You will be the voice of the customer into Capital One’s product and engineering teams for product feedback and improvements. You will play an integral role in building knowledge within the team and be part of strategic initiatives for organizational and process improvements. Ideally, you have worked in a 24x7 environment, handled all tiers of support issues and been on-call during weekends.

Key responsibilities include:

• Providing email, web, and phone support to data platform users.
• Investigating and resolving issues related to cloud and data tools.
• Documenting known solutions to internal and external knowledge base.
• Investigating, troubleshooting and triaging product support questions from end users and when necessary, escalating to the engineering team.
• Submitting well documented bugs and feature requests arising from customer submitted requests.
• Keeping up to date on unresolved issues and working towards ensuring timely resolution while working with product and engineering partners.
• Participating in weekend on-call support rotation and ability to work flexible hours if and when required.

Has a bias towards action and a proven track record of troubleshooting technical problems in a dynamic and ambiguous environment with a customer-first approach. Has an ability to influence without direct authority across partnering teams in business, technology, compliance etc., Focus on continuous improvement based on metrics and ideate to create customer-centric metrics whenever they do not exist.

Basic Qualifications:

• Bachelor’s degree in Computer Science or related field.
• 4+ years’ experience in a Technical Support or similar function.
• Experience writing, troubleshooting, and debugging advanced SQL queries.
• Good understanding of GCP, Amazon AWS or Microsoft Azure ecosystems.
• Excellent ability to troubleshoot on a variety of operating systems (Windows, Mac,
  * Nix).
• Sufficient knowledge of internet protocols such as TCP/IP, HTTP/S, SFTP, DNS as well as the ability to use diagnostic tools to troubleshoot connectivity issues.
• Good understanding of the system integration technologies and principles including ReST and SOAP.
• Must be knowledgeable with querying logging platforms such as Splunk and/or AWS logs.
• Scripting/coding experience in any of the following:
  Python, Java, .Net, NodeJS, R.

Preferred Qualifications:

• Master’s degree in Computer Science or related field.
• 5+ years experience in a Software Engineering environment.
• Experience working with big data.
• Understanding of Data Warehousing fundamentals and concepts.
• Database migration and ETL experience.
• Experience supporting applications running on either GCP, Amazon AWS or MS Azure.
• Experience with virtualization solutions (vmware, docker, virtual box, etc).
• Understanding of cloud security concepts.