QA Data Analyst

Tellius enables organizations to get faster insights and act upon cloud-scale enterprise data using AI-powered automation. Any user can ask any question across billions of records via a ChatGPT-like interface, understand “why” metrics change via AI insights that surface hidden key drivers and trends, and leverage agentic flows to perform complex multipart analysis easily — in a self-service manner. Unlike traditional BI tools, Tellius excels at ad hoc analysis, deep dives, and business-friendly advanced analytics.

Overview

​​We are an AI-powered analytics platform helping businesses make smarter and faster decisions through data. As we grow our Quality Assurance and Data team, we are looking for curious, data-driven individuals who are excited to explore the world of analytics with a quality mindset.

This role is ideal for freshers or early-career professionals who want to build a strong foundation in data validation, exploratory analysis, and QA, with exposure to real-world business use cases and a pathway toward data or QA specialization.

 Key Responsibilities:

Data Analysis & Validation (Primary Focus – 70%)

• Understand and validate analytics outputs using business rules, aggregation logic, and data consistency checks

• Perform data quality checks on structured and unstructured data sources (e.g., Excel, CSV, Google Drive, Slack).

• Use Excel and write basic SQL queries to validate backend transformations and business KPIs.

• Analyze trends, anomalies, and inconsistencies in the platform’s output to ensure accuracy.

• Work closely with Product and Data teams to ensure alignment between business logic and platform results.

• Assist in documenting test scenarios and edge cases from a data perspective.
  
  

Manual QA & Product Testing (30%)

• Design and execute test cases to validate visualizations, dashboards, filters, and search-based analytics features.

• Conduct functional and exploratory testing across web browsers and devices.

• Identify and report bugs with detailed steps, reproducibility notes, and clear logs using tools like JIRA.

• Collaborate with Engineering to clarify issues and support quick resolution.
  
  

 Exposure to QA Automation (Good to Have)

• Get introduced to automation tools like Cypress and basic test scripting.

• Contribute to regression test planning under guidance.

• Understand where automation fits in the product testing lifecycle and CI/CD flow.
  
  

Required Qualifications:

• 0–2 years of experience in data analysis, software testing, or relevant academic/internship projects.

• Bachelor’s degree in Computer Science, Statistics, Information Systems, Mathematics, or a related field.

• Strong analytical mindset, attention to detail, and a passion for working with data.

• Good communication and documentation skills.

• Willingness to learn tools for data analysis and quality validation.
  
  

 Preferred (Nice to Have):

• Working knowledge of SQL, Excel, or Python.

• Familiarity with BI tools like Power BI, Tableau, or Looker.

• Exposure to QA tools such as JIRA, Postman, or basic scripting with Cypress.

• Understanding of structured vs. unstructured data sources.
  
  

 Why Join Us:

• Work at the intersection of data analytics and quality assurance in a cutting-edge product environment.

• Opportunity to grow into roles such as Data Analyst, Product QA, or QA Automation Engineer.

• Gain hands-on experience with real datasets, business metrics, and modern web technologies.

• Be part of a collaborative team culture with strong mentorship and continuous learning.