Customer Data Analyst

Fieldguide

. Develop and customize customer-facing reports and dashboards .

Posted 11/9/2026full-timeRemote • United StatesJuniorMid-Level💰 $145,000 - $175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Advanced SQL for data extraction, transformation, and validation, alongside strong analytical skills for handling complex datasets. Proficient in developing scalable reporting solutions and collaborating with cross-functional teams to enhance data-driven decision-making.

Highest-signal resume keywords

Advanced SQL SkillsData ModelingData Quality ManagementDashboard CreationCustomer Analytics

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data AnalyticsAnalytics EngineeringData OperationsBusiness IntelligenceDimensional Data ModelingData TransformationsMetric DefinitionsData ValidationData GovernanceData Quality

Soft Skills

Excellent Communication SkillsAnalytical Skills

Tools & Technologies

Dbt

Industry Keywords

B2B SaaSEnterprise SoftwareCustomer SuccessQBRsValue RealizationProduct TelemetryCustomer Usage DataAuditAdvisoryProfessional Services

Tech Stack

Tools & technologies

SQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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