Data Analyst, Customer Success

Posted Yesterday
Hiring Remotely in North Carolina, USA
Remote or Hybrid
Mid level
Artificial Intelligence • Software
The Role
Analyze Customer Success data using SQL and Tableau to build data models, dashboards, reports, and actionable insights. Improve reporting accuracy, data quality, documentation, and operational processes across metrics such as response time, resolution time, customer satisfaction, NPS, and feature adoption. Collaborate with stakeholders, manage analytics tasks in Jira, troubleshoot data issues, and use AI-assisted tools including Cursor and Claude to improve efficiency.
Summary Generated by Built In
Description

VAST Data is looking for a Data Analyst, Customer Success to join our growing team!

This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.

"VAST's data management vision is the future of the market." - Forbes

VAST Data is the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, VAST takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.

Our success has been built through intense innovation, a customer-first mentality and a team of fearless VASTronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our company's growth and at a pivotal point in computing history.

Overview:

VAST is seeking a Data Analyst, Customer Success to join our growing analytics team. The candidate will roll up their sleeves and work hands-on to build analytics and dashboard visualizations that deliver actionable insights on core customer success metrics. The role will partner closely with stakeholders in the Customer Success organization to develop analytical solutions that improve VAST's reporting systems, data quality, and processes for metrics such as Time to Response, Time to Resolution, Customer Satisfaction, NPS, and Feature Adoption.

As a Data Analyst, Customer Success, this position will play a key role in transforming data into actionable insights that improve business outcomes. The Data Analyst will be part of teams that build and deliver accurate, accessible, and repeatable business reporting and insights to stakeholders across all levels. 

The analyst will focus on defined questions, creating standard reports and dashboards. The role will be responsible for both building data models behind operational metrics, using SQL, and creating visually compelling dashboards in Tableau. We are seeking an analyst with intellectual curiosity with a natural desire to explore data and ask questions that lead to deeper insights.

Essential Duties and Responsibilities

  • Data Extraction and Modeling: Write SQL queries to extract and transform customer success data, ensuring data integrity and accuracy for reporting and analysis purposes
  • Business Understanding: Proactively seek guidance from senior analysts and stakeholders to build deeper understanding of Customer Success processes and metrics 
  • Data Analysis: Collect, clean, and interpret data from various sources to provide actionable insights that support Customer Success objectives
  • Reporting: Develop ad-hoc reports and analytics packages for regular business reviews. Build and maintain reports in Tableau
  • Data Visualization: Develop and maintain Tableau visualizations to represent metrics, trends, and performance
  • Insights: Deliver analytics that answer key business questions and drive value and improved outcomes for Customer Success stakeholders
  • Data Management: Support efforts that improve the accuracy of reporting data. Identify data quality gaps, help improve the integrity of source data, and maintain documentation and data definitions for financial metrics. Escalate complex data issues as needed
  • AI-Enabled Efficiency: Use tools such as Cursor and Claude to speed up SQL development, documentation, and testing, and to reduce manual, repetitive analytics work
  • Process & Policy: Track and manage analytics work in Jira. Work cross-functionally to streamline data processes, troubleshoot issues, and collaborate to improve data across systems

Requirements

  • Education: Bachelor's degree in Business Analytics, Business, Computer Science, Data Science, or a related field
  • Experience: 3-5 years of experience as a data analyst; Customer Success experience preferred
  • Programming Languages: Proficient in SQL for data extraction and manipulation
  • Visualization Tools: Experience with Tableau for dashboard creation and data visualization
  • AI Tools: Some experience using AI-assisted coding and analysis tools (e.g., Cursor, Claude) to improve speed and quality of work
  • Data Visualization and Analytics: Strong analytical, problem-solving, and critical thinking skills. Proficient in BI tools like Tableau. 
  • Domain Expertise: Familiar with Customer Success workflows, KPIs, and operational lifecycles of a software company preferred but not required 
  • Project Tracking: Comfortable working in Jira to manage and track analytics tasks
  • Travel: Minimal travel required (approximately 10% or less annually)

Qualifications

  • A relentless drive and a customer-first mentality are essential.
  • An attention to detail that ensures accuracy and reliability in findings that leads to trust and credibility with stakeholders.
  • The ability to break down complex problems, identify patterns, and derive meaningful insights from data.
  • Intellectual curiosity with a natural desire to explore data and ask questions that lead to deeper insights.
  • The ability to convey data insights clearly and effectively to both technical and non-technical stakeholders.
  • Ability to manage multiple projects and deadlines while prioritizing tasks.
  • Ability to thrive in a culture of transparency and direct feedback.

Skills Required

  • Bachelor's degree in Business Analytics, Business, Computer Science, Data Science, or a related field
  • 3-5 years of experience as a data analyst
  • Proficiency in SQL for data extraction and manipulation
  • Experience with Tableau for dashboard creation and data visualization
  • Experience using AI-assisted coding and analysis tools such as Cursor or Claude
  • Familiarity with Customer Success workflows, KPIs, and software-company operational lifecycles
  • Comfort working in Jira to manage and track analytics tasks

VAST Data Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about VAST Data and has not been reviewed or approved by VAST Data.

  • Healthcare Strength Medical, dental, vision and life insurance are included, with several elements identified as employer-provided. Coverage aligns with what is commonly offered by high‑growth tech companies.
  • Leave & Time Off Breadth Time off includes generous or unlimited PTO alongside paid sick days and paid holidays, coupled with remote or work‑from‑home flexibility. This breadth supports taking time away when needed.
  • Equity Value & Accessibility Company equity is a standard part of offers with a typical four‑year vest, and professional development support is available. Equity is positioned as a meaningful component of total compensation at a growth‑stage company.

VAST Data Insights

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The Company
HQ: New York, NY
848 Employees
Year Founded: 2016

What We Do

Meet the data platform company for the AI era. Accelerating time-to-insight for workload-intensive applications, the VAST Data Platform delivers scalable performance, radically simple data management and enhanced productivity for the AI-powered world. Launched in 2019, VAST is the fastest-selling data infrastructure startup in history.

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