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.
