About Us

Fieldguide is establishing a new state of trust for global commerce and capital markets through automating and streamlining the work of assurance and audit practitioners specifically within cybersecurity, privacy, and financial audit. Put simply, we build software for the people who enable trust between businesses.

We’re based in San Francisco, CA, but built as a remote-first company that enables you to do your best work from anywhere. We're backed by top investors including Growth Equity at Goldman Sachs Alternatives, Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, DNX Ventures, Global Founders Capital, Justin Kan, Elad Gil, and more.

We value diversity — in backgrounds and in experiences. We need people from all backgrounds and walks of life to help build the future of audit and advisory. Fieldguide’s team is inclusive, driven, humble and supportive. We are deliberate and self-reflective about the kind of team and culture that we are building, seeking teammates that are not only strong in their own aptitudes but care deeply about supporting each other's growth.

About the Role

Fieldguide is looking for a Customer Data Operations Analyst to help build and operationalize the data foundation that connects how customers use Fieldguide with how we measure, understand, and communicate the value they receive from the platform.

This role will sit at the intersection of Customer Success, Product, Data Science, and GTM Operations, translating real-world customer needs into scalable data models, trusted reporting, and actionable insights. The role will combine strong SQL and analytics capabilities with hands-on data modeling and reporting, ensuring customer data is accurate, accessible, and built to scale.

While this role will participate in select customer meetings, QBRs, and onsite engagements to understand reporting requirements firsthand, the majority of the role will be hands-on—developing and customizing reports, querying and validating data, building and maintaining data models, and addressing gaps in the underlying data infrastructure. You will then partner with Product and Data Science to ensure the right information is captured, structured, validated, and surfaced consistently.

The goal is to create a trusted customer data foundation that enables Fieldguide and its customers to answer critical questions around product adoption, engagement, efficiency, time savings, ROI, value realization, and business outcomes.

What You'll Own

Customer Data Reporting & Insights

Own the development and customization of customer-facing reports and dashboards, translating customer requirements into accurate and actionable reporting.

Use SQL and existing data infrastructure to investigate customer questions, validate reported metrics, and resolve discrepancies.

Build scalable reporting solutions that can be reused across customers, service lines, and engagement types.

Partner with Customer Success to support data-driven QBRs, executive business reviews, renewals, and value realization conversations.

Identify where customer-specific reporting requests reveal broader gaps in Fieldguide's underlying data models or product reporting capabilities.

Work with Product and Data Science to move frequently requested reporting from manual/custom analysis toward standardized and productized capabilities

Data Modeling & Analytics

Develop and maintain scalable data models that support customer reporting, QBRs, value realization, and product analytics.

Write advanced SQL to extract, transform, validate, and analyze customer and product data across multiple data sources.

Build and maintain data models and transformations to create reliable, reusable downstream datasets.

Identify gaps in existing data models and address legacy data quality, modeling, and structural issues that impact reporting accuracy.

Translate recurring one-off reporting requirements into standardized, scalable data models and reporting infrastructure.

Partner with Data Science and Data Engineering to determine when customer reporting requirements should be addressed through analytics, data modeling, upstream product instrumentation, or broader infrastructure changes.