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.

• Establish reusable datasets and semantic definitions that enable consistent reporting across customers rather than recreating logic for individual accounts.

• Reduce manual and one-off reporting by identifying opportunities for automation and standardized reporting.

What Success Looks Like

Success in this role means Fieldguide has a trusted, scalable customer data foundation rather than relying on fragmented or one-off analysis.

• Customer-facing metrics have clear definitions, sources, methodologies, and owners.

• Customer teams can confidently use data in QBRs and executive conversations.

• Product usage and customer outcomes can be connected to measurable value.

• Data discrepancies are identified and addressed at their source.

• Customer feedback systematically informs Product and Data priorities.

• Recurring customer data requests become standardized and automated where possible.

• Fieldguide can increasingly demonstrate defensible ROI and value realization.

• Customer reporting becomes consistent across QBRs, renewals, and strategic engagements.

• Product and Data teams have a clear understanding of the information customers need from Fieldguide.

What We're Looking For

• 2+ years of experience in Data Analytics, Analytics Engineering, Data Operations, Business Intelligence, Customer Analytics, or a related technical data role.

• Advanced SQL skills with demonstrated experience querying, transforming, validating, and troubleshooting complex datasets.

• Strong understanding of dimensional data modeling, data transformations, metric definitions, and analytics architecture.

• Strong understanding of data quality, validation, governance, and operational workflows.

• Ability to translate business and customer questions into structured data requirements.

• Strong analytical skills and comfort working with large or complex datasets.

• Experience creating dashboards, reports, and executive-level data narratives.

• Excellent communication skills, particularly the ability to translate between technical and non-technical stakeholders.

Nice to Have

• Experience at a B2B SaaS or enterprise software company.

• Hands-on experience with dbt, including building, maintaining, testing, and documenting scalable data models.

• Experience supporting Customer Success, QBRs, value realization, or customer analytics.

• Familiarity with audit, advisory, accounting, or professional services workflows.

• Experience working with product telemetry and customer usage data.

• Experience partnering directly with Data Science or Analytics Engineering teams.

• Fearless - Inspire & break down seemingly impossible walls.

Some of our benefits include:

• Competitive compensation packages with meaningful ownership

• Flexible PTO

• 401k

• Wellness benefits

• Technology & Work from Home reimbursement

• Flexible work schedules