Sr. Data Analyst, Operational Intelligence
Quickbase (company site, opens in a new tab)5–9 yrsBengaluruHybridDirect career pageEst. 18–30 LPA
Posted on 2 Sept
Reach people at Quickbase
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Quickbase you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own the analytics roadmap and data models for the Pave product-led growth (PLG) funnel and associated Sales domain, including defining and measuring key metrics like trial volume, activation, conversion, and retention.
- Design, build, and maintain Snowflake data models and dbt workflows supporting PLG and Sales analytics while ensuring high standards of testing, documentation, and cross-team alignment.
- Serve as senior analytics partner to Sales and Revenue Operations leadership, providing actionable insights from ambiguous business questions and driving consensus on metric definitions across stakeholders.
Minimum Requirements
- 5 to 9 years of experience in data analytics, business intelligence, or GTM/sales analytics with domain ownership experience.
- Expert SQL skills and strong dimensional data modeling experience on cloud platforms, ideally Snowflake.
- Hands-on dbt experience including model design, testing, dependency management, and code review.
- Experience supporting Sales, Revenue Operations, or GTM teams in a SaaS environment with involvement in business reviews and forecasting; located in Bangalore, India (Hybrid).
Ideal Candidate Profile
- Experienced in product-led growth analytics within SaaS organizations, able to independently scope ambiguous problems and deliver data-driven business impact.
- Strong collaborator and influencer able to resolve conflicting metric definitions and maintain trustworthiness of critical sales and product data among cross-functional teams.
- Technically proficient in building scalable, reusable analytics models and mentoring other analysts, with a balance of close partnership with Data Engineering and business stakeholders.