Customer Engineer – Serverless Native Data Infrastructure – AWS – Bash/Python

Your ability to quickly assess and identify technical issues will be of paramount significance, as will

your ability to resolve them or suggest workarounds. In order to do so, you must make it a priority to

proactively master all facets of our product suite.

As part of the Customer Experience team, you may also participate in conducting training sessions

and professional service engagements. As a result of your efforts, you will produce field-developed

utilities and technical notes which will benefit many other departments including sales,

marketing, and product management. You are instrumental to the customer journey and growth of

the company.

This is an individual contributor role and will not formally manage other people.

Job Location



You have 2+ years of demonstrated experience as a Customer Engineer doing Tier 1 or Tier 2 support work. 

About you

Mandatory Skills 

  • You have a strong working knowledge of AWS Services.
  • You have hands-on experience with Redshift, Athena, GDC, S3, EC2, Kinesis, SNS,
  • DynamoDB, Batch, etc.
  • You have good communication and presentation skills, both written and verbal.
  • Great customer service skills and a sense of urgency

Highly Desirable Skills 

  • You have hands-on experience with one of the scripting languages like Bash, JavaScript, Python, etc.
  • Working knowledge of AWS ECS, VPC, Snowflake, etc.
  • Great debugging, problem solving, and analytical skills
  • Startup experience is highly desirable


  • Diagnose and reproduce customers’ technical issues quickly and in an expedient manner while trying to get to root cause analysis.
  • Solve complex technical challenges related to the product, and provide guidance related to data pipeline management
  • You are the first line in our Customer Experience team to help our users get the most from us. You’ll field incoming questions, help users to understand how to use the features of the product.
  • Maintain deep understanding of AWS Data and Analytics ecosystem and how to position our product in relation to other technologies.
  • Be flexible with work hours to cover Support SLA commitments.

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