At Quickbase, we help organizations build better ways to run their operations. Our products give teams the flexibility to create applications around how their work actually happens, connecting people, information, and processes so they can keep work moving as needs change.

For more than 25 years, organizations have turned to Quickbase to solve operational challenges that off-the-shelf software wasn't built for. Today, we’re building on that foundation with new products and new possibilities for how people create, adapt, and improve the systems their work depends on.

Working at Quickbase means helping find better ways forward. We’re a team of curious, collaborative people who care about solving problems, learning as we go, and building things that make work better for our customers and each other.

Senior Data Analyst, Operational Intelligence

Location: Bangalore, India (Hybrid)

Team: Operational Intelligence, Data & Analytics

Business Unit Focus: AWE (Agentic Work Evolution), with an emphasis on Pave

Company: Quickbase

Overview

Quickbase is seeking a Senior Data Analyst, Operational Intelligence to own analytics for our product-led growth motion and the Sales organization that supports it, with a primary focus on Pave, our AI-native app builder.

This role sits on our centralized Operational Intelligence team and operates as the senior analytics owner for a defined domain. You will not be handed a backlog of report requests. You will be expected to understand where the PLG motion is working and where it is not, decide what needs to be measured, build the models and reporting that answer it, and drive the definitions to consensus across Sales, Revenue Operations, Product, and Data Engineering.

Pave goes to market as a product-led motion with a light sales assist. Trialers self-serve into the product, and our Growth Advisors engage only on product-qualified signals. That means the quality of our product qualified lead logic, our activation measurement, and our conversion analytics directly determines where a small sales team spends its time. The person in this seat has an outsized influence on that.

The ideal candidate is an expert SQL and data modeling practitioner who is equally comfortable being handed an ambiguous business problem and a blank page. You bring strong judgment about what is worth measuring, the communication skills to defend a definition in a room of stakeholders who disagree, and the instinct to raise the quality bar for everyone around you.

Scope and Level

This is a senior individual contributor role. It carries ownership, not just execution.

• You own the analytics roadmap for the PLG and Sales domain, including deciding what gets built, what gets deprecated, and what gets pushed back on.

• You are the person Sales and Revenue Operations leadership come to directly with an unstructured question, and you are trusted to scope it yourself.

• You set modeling and documentation standards for your domain and review the work of other analysts against them.

• You mentor analysts on the team through code review, pairing, and design feedback, and you help raise the bar on how the team works.

• You represent Operational Intelligence in cross-functional forums and are accountable for the trustworthiness of the numbers presented there.

What You'll Do

• Own the definition and measurement of the Pave PLG funnel end to end, including trial volume, activation, published app rate, invited user rate, trial to paid conversion, retention, and expansion signals.

• Own and evolve the product qualified lead model, including the logic that determines which trialers surface to Growth Advisors, and continuously validate that the signals we act on actually predict conversion.

• Design and build the Snowflake data models that support Sales and PLG analytics, making architectural decisions about grain, conformed dimensions, and how the PLG and CRM domains join together.

• Author and review dbt pull requests that extend the central governed data layer, holding a high standard for testing, documentation, and alignment with enterprise modeling patterns.

• Serve as the senior analytics partner to Sales, Revenue Operations, and Growth leadership, translating ambiguous business questions into scoped analyses and pushing back when the question being asked is not the question that matters.

• Drive metric definitions to organizational consensus, resolving conflicting definitions across teams and documenting the agreed source of truth.

• Deliver analyses that change decisions, not just dashboards that report them, including conversion driver analysis, cohort and retention studies, and segment level performance breakdowns that inform where Growth Advisors and Product should focus.

• Partner closely with Data Engineering on pipeline dependencies, data quality practices, and modeling standards, and act as the informed voice of the business when trade-offs need to be made.

• Support operating mechanisms including GTM business reviews, weekly forecast reviews, and state of the business reporting, where accuracy and timeliness are non-negotiable.

• Build self-service foundations by producing reusable, well-documented datasets and semantic models that let stakeholders answer their own recurring questions.

• Establish and monitor data quality controls across Sales and product analytics workflows, and own remediation when something breaks.

• Mentor other analysts and contribute to the technical growth of the Operational Intelligence team.

What You Bring

• 5 to 9 years of experience in data analytics, business intelligence, or GTM and sales analytics, including clear ownership of an analytics domain rather than delivery against someone else’s backlog.

• Expert SQL skills and strong dimensional data modeling ability, with substantial hands-on experience in a cloud data platform, ideally Snowflake.

• Hands-on dbt experience at depth, including designing models, writing tests, managing dependencies, and reviewing other people’s pull requests.

• Demonstrated experience supporting Sales, Revenue Operations, or GTM teams in a SaaS environment, including direct exposure to business reviews, forecast cadences, and leadership stakeholders.

• Solid working knowledge of PLG concepts and product usage analytics, including funnel measurement, activation, product qualified leads, and trial conversion.

• A track record of taking an ambiguous business problem, scoping it independently, and delivering an answer that changed a decision.

• Proven ability to define and standardize business metrics across stakeholder groups, including navigating disagreement and landing on a documented definition people actually use.

• Strong written and verbal communication, with the ability to present clearly to senior stakeholders and to say no with a reason.

• Comfort working cross-functionally in a globally distributed, async-friendly environment, with meaningful overlap with US business hours.

Nice to Have

• Experience with Power BI or comparable BI and data visualization tools.

• Experience with Salesforce CRM data and revenue analytics platforms.

• Familiarity with product analytics platforms such as Amplitude, Mixpanel, or Pendo.

• Experience building or maintaining a semantic layer or metrics layer.

• Exposure to data governance, data cataloging, and data quality frameworks.

• Familiarity with AI-assisted analytics workflows, such as Snowflake Cortex or LLM-based classification of unstructured data.

• Python for data work, including pandas and lightweight pipeline scripting.

• Experience in a product-led or hybrid sales-led and PLG SaaS organization.

Why This Role Matters

Pave is a newly launched, fast-moving growth motion for Quickbase, and it is being run on learning velocity. Decisions about where the product goes and where a small sales team spends its time are made on the strength of the data underneath them.

Sitting on a centralized Operational Intelligence team gives you an unusual vantage point. You are close enough to Data Engineering to shape how the data is built, and close enough to the business to know what it is for. That combination is where the leverage in this role comes from, and it is why we are hiring at a senior level rather than a junior one.

What Success Looks Like

In the first six months

• You have built a working understanding of the Pave funnel and the systems behind it, and you can explain where the data is trustworthy and where it is not.

• You have taken ownership of at least one core measurement area, such as activation or product qualified leads, and improved it.

• Your dbt contributions are merged, tested, documented, and aligned with enterprise standards without needing heavy review.

• Sales and Revenue Operations stakeholders come to you directly rather than routing through your manager.

In the first twelve months

• Key GTM and PLG metrics are clearly defined, documented, and trusted across the organization, with disagreements resolved rather than tolerated.

• The product qualified lead model demonstrably improves how Growth Advisors prioritize their time, backed by measured outcomes.

• Self-service reporting adoption has grown, and the volume of ad hoc requests reaching the team has measurably fallen.

• You have influenced at least one significant business or product decision through analysis you scoped yourself.

• Other analysts on the team are better at their jobs because of standards, review, or mentorship you provided.

• Strong, durable working relationships exist with Data Engineering, Revenue Operations, and the Growth Advisor team.

How We Think About AI
At Quickbase, we view AI as a tool to accelerate how work gets done — not replace it. We encourage thoughtful use of AI to improve speed, quality, and decision-making, while maintaining strong judgment, accountability, and data integrity.

Equal Opportunity Statement

Quickbase is committed to building a diverse and inclusive workplace. We encourage candidates from all backgrounds to apply – even if you don’t meet every qualification listed. We are proud to be an equal opportunity employer.

Benefits

• Modern Health
• Group Medical Insurance
• Night Shift Allowance
• Hybrid Work Allowance
• Mobile and Internet Allowance
• Meal Benefit
• Office Transportation
• On-Call Weekend Allowance
• Weekend Working Allowance
• Employee Referral Bonus