Data Analyst (Remote)

• Location: United States
• Workplace: Remote
• Employment Type: Full Time
• Experience: 2-3+ years of analytics experience

Core Areas: Revenue Analytics, Sales Analytics, SQL, dbt, Predictive Modeling, Business Intelligence, Revenue KPIs, Data Quality

Compensation: $145,000-$170,000 per yeary

About the Role

This opportunity is for a Data Analyst who will own Sales Analytics and turn raw data into actionable insights that influence strategy, headcount, territories, compensation, resource allocation, and day-to-day sales execution. The position will analyze revenue performance, pipeline quality, forecast accuracy, retention, account behavior, and other critical business metrics while partnering directly with senior operators.

The role works across Snowflake, dbt, Metabase, Tableau, and Hex to build reliable data models, reporting, dashboards, and predictive analytics. It requires strong SQL, structured analytical thinking, clear communication, and the ability to translate ambiguous business questions into rigorous analysis that supports revenue planning and go-to-market decisions.

What You'll Do

Strategic and Predictive Initiatives

• Design and maintain predictive models that help anticipate revenue outcomes, retention patterns, and account behavior.
• Create analytical frameworks that score or segment accounts based on potential, risk, or lifecycle signals.
• Develop analytical tools that improve resource allocation, account prioritization, and identification of emerging trends.
• Incorporate new data sources and enrichment methods to strengthen understanding of the market and customer base.
• Lead cross-functional efforts that translate analytical findings into changes in processes, priorities, and go-to-market strategy.
• Drive long-term analytics initiatives that improve the accuracy, reliability, and scalability of decision-making.

Performance and Growth Analytics

• Own core revenue KPIs, operating results, and weekly performance reporting.
• Build and maintain dashboards covering quota, attainment, pipeline health, retention, and other key performance metrics.
• Calculate monthly and quarterly incentive compensation for revenue teams.
• Support quarterly planning with analysis related to quota, capacity, coverage, and segmentation.
• Conduct deep-dive analysis of pipeline performance, forecast accuracy, conversion rates, churn drivers, and competitive performance.
• Perform segment and industry analysis to identify growth opportunities and performance gaps.
• Conduct root cause analysis when key metrics change unexpectedly.
• Provide clear, concise insights for leadership reviews, quarterly planning, and forecast discussions.

Data Modeling and Infrastructure

• Build and maintain clean, reliable data models in dbt.
• Develop metric definitions, documentation, and analytical logic that keep reporting consistent across the organization.
• Improve data quality by identifying inconsistencies, missing fields, and data model issues.
• Automate recurring reporting through scalable pipelines and reusable data models.
• Maintain data integrity across analytics platforms and reporting workflows.

Storytelling and Influence

• Translate complex data into simple, compelling narratives for senior leaders.
• Communicate technical findings and analytical concepts clearly to non-technical audiences.
• Create visualizations and written insights that improve clarity and support decision-making.
• Strengthen analytical practices by maintaining a high standard for communication, documentation, and analytical rigor.

Qualifications

Required Experience

2–3+ years of professional experience in analytics, preferably supporting Sales, Revenue Operations, Customer Success, or lifecycle analytics.

Required Skills

• Strong SQL skills and experience working with data in a warehouse environment.
• Experience using Tableau, Metabase, or a similar business intelligence platform.
• Experience using AI-assisted tools such as Claude or Cursor as part of analytical workflows.
• Ability to independently translate loosely defined business questions into structured analytical approaches.
• Strong communication skills with an emphasis on clarity and directness.
• Ability to balance recurring operational reporting with longer-term analytical initiatives.
• Ability to operate effectively in a fast-paced, high-growth environment.

Education & Certifications

Bachelor's degree in a STEM field with strong academic performance.

Preferred Qualifications

Exposure to Python or professional experience using Python for analytics.