Sales Analytics Architect

Socket.dev; San Francisco (CA); Hybrid; USD 86,000 - 102,000; Full time

Job summary

Fin is seeking a Sales Data Analyst in the San Francisco Bay Area to join our Sales Operations and GTM Analytics team. You will build data models, dashboards, and compensation outputs to help leadership understand rep performance and productivity.

You'll partner with Finance, Data Engineering, and Business Systems to translate complex rules into reliable analyses, while exploring AI-driven improvements. This role offers hybrid work and opportunities to influence go-to-market outcomes.

Qualifications

• 0-2 years of experience in sales analytics, sales operations, business analytics, finance, data analysis, or a related field.
• A technical or quantitative background and an interest in working with data, systems, and business processes.
• Basic to intermediate SQL skills, with the ability to query, join, aggregate, and validate data across multiple sources.
• Experience with Excel or Google Sheets; familiarity with BI or visualization tools such as Tableau, Looker, or Power BI is a plus.
• Strong attention to detail and a commitment to data accuracy, particularly when working with compensation and performance metrics.
• Interest in sales performance, forecasting, compensation, productivity, and go-to-market operations.
• Ability to communicate analytical findings clearly to both technical and non-technical audiences.
• Strong collaboration skills and comfort partnering with Sales, Finance, Data Engineering, Business Systems, and other cross-functional teams.
• AI fluency: curiosity about using AI to improve analytical workflows, paired with the judgment to validate AI-generated logic, numbers, and recommendations.
• A growth mindset, intellectual curiosity, and willingness to ask questions, learn quickly, and take ownership of well-defined work.
• Comfortable and energized operating in a fast-moving organization where priorities and business questions evolve.

Responsibilities

• Own and maintain foundational sales analytics data models, partnering with Data Engineering to build new models and improve data quality.
• Build, maintain, and improve recurring reports and dashboards for sales metrics, attainment, productivity, and business performance.
• Build and support sales compensation models, including the reporting required to track rep performance and attainment.
• Partner with Finance and Sales Operations to translate compensation plans, business rules, and metric definitions into reliable analytical outputs.
• Analyze sales performance trends, variances, and data-quality issues to identify risks, opportunities, and areas for improvement.
• Support reporting and analysis for recurring sales operating cadences, including weekly, monthly, and quarterly business reviews.
• Work with Data Engineering and Business Systems to define requirements, troubleshoot reporting issues, and test improvements to sales data and systems.
• Document data definitions, model logic, reporting processes, and assumptions so that stakeholders can confidently use and interpret our metrics.
• Partner with Sales, Finance, Operations, and Engineering stakeholders to turn ambiguous questions into clear, data-backed recommendations.
• Use AI tools to accelerate analysis, modeling, documentation, and problem-solving while applying sound judgment and validating outputs before they inform business decisions.
• Identify opportunities to improve the scalability, accuracy, and efficiency of sales reporting and analytics processes.

Skills

SQL

Excel

Tableau

Looker

Power BI

Job description

Fin is seeking a Sales Data Analyst in the San Francisco Bay Area to join our Sales Operations and GTM Analytics team. You will build data models, dashboards, and compensation outputs to help leadership understand rep performance and productivity.

You'll partner with Finance, Data Engineering, and Business Systems to translate complex rules into reliable analyses, while exploring AI-driven improvements. This role offers hybrid work and opportunities to influence go-to-market outcomes.