The Role

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.

What You’ll Be Doing

GTM Data Infrastructure & Pipeline Development

- 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, market

📌 GTM Analytics Engineer (Bellprat)
🏢 Affinity.
📍 Bellprat