Data Solutions Lead Engineer - Panoply

SQream Technologies

United States of America
  • Job Type: Full-Time
  • Function: Data Science
  • Industry: Data Analytics & Infrastructure
  • Post Date: 03/16/2023
  • Website:
  • Company Address: 7 World Trade Center, 250 Greenwich Street, New York, 10007
  • Salary Range: $50,000 - $150,000

About SQream Technologies

SQream provides an analytics platform that minimizes Total Time to Insight (TTTI) for time-sensitive data, on-prem and on-the-cloud. Designed for tera-to-peta-scale data, the GPU-powered platform enables enterprises to rapidly ingest and analyze their growing data – providing full-picture visibility for improved customer experience, operational efficiency, and previously unobtainable business insights.

Job Description

Panoply by SQream is looking to hire a passionate and enthusiastic Data Solutions Lead Engineer to partner with our prospects and customers to ensure they experience the full potential of the platform. This is an end-to-end role where you will support Account Executives to close new business and identify opportunities to retain, renew and upsell customers 

The ideal candidate is a subject matter expert in reading and writing SQL and is empathic to the customer’s needs through written and verbal communication. If this describes you then please apply. 

We look forward to meeting you and having you join our exceptional team!

Job brief:

A Data Solutions Lead Engineer at Panoply by SQream is a hybrid role and focuses on three key areas of the customer journey:

Proactive customer outreach (40% of your time)

  • Monitor customer usage data and contact customers to ensure customer retention and identify upsell/cross-sell potential
  • Partner with the customer to provide data warehousing best practices, solve technical issues, and optimize the data pipeline.
  • Build educational resources to teach our customers ELT, data warehousing, and analyzing best practices

Support Engineering (40% of your time)

  • Provide creative solutions and industry-leading support to customers
  • Create in-depth bug reports in JIRA
  • Communicate issues to relevant teams

Sales Engineering (20% of your time)

  • Work alongside the Account Executive to demonstrate the value of Panoply throughout the sales cycle, answer technical questions, and create POCs for prospects.


  • Be the technical expert about Panoply - know the in and outs of our platform, how our system works, and the underlying technologies we are built on (Redshift and Google BigQuery).
  • Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Panoply in relation to them.
  • Be the go-to contact for technical problems for our users.
  • Help onboard prospects and new customers to the Panoply platform, providing best practices and answering technical questions along the way.
  • Conduct data reviews and support calls with prospects and customers to share solutions and increase usability, performance, and value.
  • Create content that answers common questions asked by our users.
  • Be the voice of our users - advocate for features that would help to improve the customer’s experience.
  • Always be learning and looking to expand your technical knowledge.



  • Previous experience as a Customer Sucess Engineer, Support Engineer, Technical Account Manager, Sales Engineer, or similar roles.
  • Bachelor’s Degree in Computer Science, Information Technology, or another relevant field. Relevant work experience may fulfill this requirement.
  • Ability to diagnose and troubleshoot technical issues, provide creative solutions, and communicate them to non-technical users in both verbal and written form.
  • Deep knowledge of SQL (e.g. window functions, CTEs, materialized views, query optimization, etc).
  • Intermediate to advanced knowledge of Python.

Previous experience working with:

  • Terminal/Command Line
  • Relational database technologies

Nice to Have:

Previous experience working with:

  • Redshift or Google BigQuery
  • PostgreSQL
  • NoSQL database technologies (e.g. MongoDB, DynamoDB, etc.)
  • AWS (e.g. S3, CloudWatch, etc)
  • GCP (e.g. Cloud Storage, Cloud Logging, etc)
  • JIRA
  • Salesforce

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