Academy - GTM Business Analyst & Business Intelligence

Job Summary

The Academy
-GTM Business Analyst & Business Intelligence role sits at the center of our Cloud Customer Success data transformation. You will work directly with the Director of Strategy & Operations to architect and operationalize the GTM Data Engine, a connected intelligence system that links the full customer lifecycle across all Cloud products, enabling CS leaders and field teams to make faster, more confident, data‑driven decisions.

This is a builder role. You will be responsible for designing the data foundation, surfacing actionable insights, and embedding AI-powered systems that scale customer success strategy, operational planning, and performance management across the entire organization.

Data Engine Architecture & Foundation

• Partner with the Director of Strategy & Operations to define the end-to-end architecture of the GTM Data Engine
• Connect sales, CS, Rev Ops, and product usage data across Cloud product offerings
• Design and maintain scalable data models, taxonomies, and pipelines supporting customer health scoring, risk analysis, migration tracking, and KPI metrics
• Establish a single source of truth for CS performance data to eliminate fragmented reporting across tools and teams
• Lead data governance practices including definitions, lineage, quality standards, and access controls

Business Intelligence & Reporting

• Build and own executive‑ready dashboards (MBRs, QBRs, board‑level views) using tools like Power BI and Salesforce reports
• Develop self‑serve reporting frameworks to enable leaders to access insights independently from the data team
• Translate complex datasets into clear narratives by visualizing trends, identifying anomalies, and linking metrics to strategic outcomes
• Own KPI tracking for customer success performance indicators including CSAT, migration velocity, time‑to‑value, digital engagement, and 1:many coverage ratios (team productivity)

AI-Powered Systems & Automation

• Leverage AI tools such as Copilot, Gemini, NotebookLM, and Cursor to accelerate data analysis, insight generation, and documentation workflows
• Build AI‑assisted playbooks, scoring models, and alert systems to proactively identify at‑risk accounts, expansion signals, and migration blockers
• Design and implement prompt engineering frameworks for repeatable, AI‑augmented analytics workflows
• Partner with CS leadership to identify automation opportunities in operational processes and integrate AI into M /Q  preparation cycles

Strategic Analysis & Operational Planning

• Conduct deep‑dive analyses supporting FY planning cycles, headcount modeling, coverage model design, and GTM segmentation decisions
• Support in preparing executive presentations, strategy decks, and cross‑functional deliverables by translating data into executive‑ready storylines
• Monitor leading indicators and provide forward‑looking analysis to enable proactive CS operations rather than reactive reporting
• Serve as the intelligence layer for cross‑functional partners including Sales, Rev Ops, BA/BI, Product, and IT

Cross‑Functional Collaboration & Stakeholder Enablement

• Act as the embedded data partner for CS leaders across all BUs
• Understand their business context and translate operational questions into analytical solutions
• Collaborate with Rev Ops and BA/BI teams on data infrastructure alignment, architecture decisions, and tool integrations
• Facilitate working sessions to define business requirements, validate metric definitions, and align stakeholders on data standards
• Mentor CS team members on data literacy, self‑serve tooling, and evidence‑based decision making

SKILLS & QUALIFICATIONS

• Advanced SQL, BI, and data visualization expertise
• Experience with data warehouses, ETL tools, and Salesforce ecosystems
• Proficiency in Python/R, Excel, and AI‑enabled analytics
• Ability to build dashboards, automate insights, and drive self‑service reporting
• Strong executive communication and data storytelling skills through presentations and strategic recommendations

• Demonstrated experience building analytics products or data systems from the ground up (not just maintaining existing infrastructure)
• Experience working directly with senior leadership and…