GTM Analytics Engineer

The GTM Analytics Engineer designs, implements, and maintains scalable data infrastructure to enable analytics and reporting. Responsibilities center on the development, management, and governance of GTM (Finance, Marketing, Sales, CS) BDM Data architecture, GTM pipeline integration, data quality assurance, and the secure operation of BI tools across the GTM organization. This role reports to the Director of Revenue Operations., * Manage all data models in dbt using version control (Git/GitHub), with pull-request review, automated testing, and CI/CD deployment pipelines.

• Write and maintain dbt tests (schema, data, and unit tests) and enforce them in CI to catch regressions before they reach production.
• Use AI-assisted development tools (e.g., Cursor, Claude) to accelerate modeling, refactoring, code review, and documentation.
• Establish and enforce data modeling standards, including naming conventions and calculation methodologies
• Design and optimize Business Dimensional Model (BDM) tables aligned with business requirements in dbt.
• Develop, automate, and maintain GTM data pipelines, ensuring delivery for business analytics
• Build and maintain reusable semantic layers with standardized metric definitions and business logic and YML files.
• Perform user acceptance testing and continuously refine pipelines for performance and scalability

Data Governance and Pipeline Performance

• Establish data quality controls (audits, logging, root cause analysis, automated cleansing) to ensure accuracy, reliability, and compliance throughout all data flows.
• Implement monitoring and alerting for data pipeline performance (timing, error rates, duplication), maintaining SLAs, and proactive issue resolution.
• Govern access and controls for sensitive customer, marketing, and product data, ensuring compliance with privacy regulations and security standards.

Collaboration & Documentation

• Partner with analysts, data scientists, and stakeholders to deliver curated datasets, communicate data limitations, and support ad hoc data requests.
• Maintain comprehensive documentation, including lineage tables, schema definitions, performance logs, and operational procedures for BDM and GTM solutions.

AI Solutioning and Management

• Design and maintain AI-ready data models and semantic definitions that let LLMs query GTM data accurately and safely.
• Integrate warehouse data into AI tools (e.g., Claude via MCP) to enable natural-language analytics, reducing reliance on static dashboards.
• Build and maintain reusable AI skills, prompts, and agents that automate recurring analytics and data-ops tasks.
• Partner with stakeholders to identify workflows where AI can replace manual reporting, and prototype/ship those solutions.
• Establish guardrails, evaluation, and governance for AI-driven data access (scope, accuracy, sensitive-data handling)., * We live our values: As owners, we take pride in everything we do. We embrace a growth mindset, engage in respectful candor, act as playmakers, and "taste the soup" by diving deep into experiences to create the best outcomes for our colleagues and clients.
• Health Benefits: Comprehensive health insurance for both you and your family.
• Learning & Development: We provide an annual education budget and a comprehensive L&D program.
• Wellness Support: We provide a monthly budget for wellness memberships/equipment to support your overall health and happiness.

• Proficiency with data pipeline development, SQL, and cloud data warehousing (Snowflake, BigQuery, Redshift, etc.), including ingesting and transforming Salesforce data via APIs or native connectors.
• Strong dbt experience - modeling, testing, and managing projects in a version-controlled, CI/CD workflow (Git/GitHub).
• Proficiency with AI-assisted development and analytics tools (e.g., Cursor, Claude/LLMs) and interest in AI-native data workflows.
• Familiarity with integrating data warehouses into AI/LLM tooling (e.g., MCP, semantic layers for AI consumption) - a strong plus.
• Experience designing and managing Business Data Models (BDM) for data warehouse environments, incorporating Salesforce objects (Accounts, Opportunities, Campaigns) for analytics and reporting.
• Hands-on experience with Salesforce data management, including SOQL, schema understanding, and troubleshooting sync issues.
• Strong communication and collaboration skills, with the ability to partner with Sales, Marketing, and RevOps teams.