Customer Data Analyst

Job not on LinkedIn

🔥 24 minutes ago

🇺🇸 United States – Remote

💵 $145k - $175k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

📉 Data Analyst

🚫👨‍🎓 No degree required

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 20%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Fieldguide

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

🏥 Healthcare

🤖 Artificial Intelligence

Consulting • Healthcare • Artificial Intelligence

Fieldguide is a modern, award-winning AI platform designed for advisory and audit firms. It helps streamline engagements, increase efficiency, and improve client satisfaction through its end-to-end engagement analytics. The platform supports various services, including risk advisory, cybersecurity and privacy, regulatory compliance, SOC readiness and audits, IT audits, and financial audits. Fieldguide integrates with popular productivity and IT tools to provide a seamless user experience, allowing for automated management of requests, documents, and reports. Trusted by top industry firms, Fieldguide enhances the practice of audit and advisory services with AI-driven innovations that save time and improve margins.

📋 Description

• Develop and customize customer-facing reports and dashboards • Translate 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 reusable 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 gaps in underlying data models and product reporting capabilities • Work with Product and Data Science to standardize and productize frequently requested reporting • Develop and maintain scalable data models supporting customer reporting, QBRs, value realization, and product analytics • Write advanced SQL to extract, transform, validate, and analyze customer and product data across multiple sources • Build and maintain data models and transformations for reliable, reusable downstream datasets • Address legacy data quality, modeling, and structural issues affecting reporting accuracy • Establish reusable datasets and semantic definitions for consistent cross-customer reporting • Identify automation and standardization opportunities to reduce manual reporting • Participate in select customer meetings, QBRs, and onsite engagements to understand reporting requirements • Partner with Data Science and Data Engineering on analytics, modeling, instrumentation, and infrastructure decisions

🎯 Requirements

• 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 • Experience at a B2B SaaS or enterprise software company is a nice to have • Hands-on experience with dbt is a nice to have • Experience supporting Customer Success, QBRs, value realization, or customer analytics is a nice to have • Familiarity with audit, advisory, accounting, or professional services workflows is a nice to have • Experience working with product telemetry and customer usage data is a nice to have • Experience partnering directly with Data Science or Analytics Engineering teams is a nice to have • Must complete required application questions about dbt models, data validation, and audit and assurance automation interest • Must answer whether visa sponsorship will be required for employment in the United States

🏖️ Benefits

• Competitive compensation packages with meaningful ownership • Flexible PTO • 401k • Wellness benefits • Technology & Work from Home reimbursement • Flexible work schedules • Equity

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