Analytics Engineer, GTM Analytics

Analytics Engineer, GTM Analytics At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As GTM’s first Analytics Engineer, you'll build the foundational data infrastructure that enables trusted, scalable insights across our go-to-market organization. Embedded within our GTM Analytics team, you'll design and implement our semantic layer and data mart architecture, transforming raw data into governed, reusable models that serve as the single source of truth for critical business metrics. This role sits at the powerful intersection of data engineering and business analytics. You'll partner closely with GTM Analysts who bring deep business context, Finance teams who rely on metric alignment, and Data Engineering teams who maintain our platform. Your work will directly enable self-service analytics, reduce metric fragmentation, and lay the groundwork for AI-powered insights that drive revenue decisions. What you’ll do as an Analytics Engineer at Vanta: - Build Revenue Data Marts: Design and implement dbt-based data marts for core GTM metrics (ARR, NRR, GRR, pipeline, quota, bookings), ensuring 100% reconciliation with Finance's source of truth - Establish Semantic Layer: Encode business logic and metric definitions into a governed, version-controlled semantic layer that standardizes how Vanta defines and calculates key metrics - Partner with GTM Analysts: Translate business requirements from analysts who understand stakeholder needs into scalable, well-tested data models that enable self-service insights - Drive Metric Governance: Collaborate with Finance, RevOps, and business leaders to resolve definitional conflicts, establish clear ownership of metrics, and maintain cross-functional alignment on KPIs - Enable AI-Powered Analytics: Create clean, well-documented datasets that can safely power AI assistants, advanced analytics, and automated reporting tools - Influence Platform Roadmap: Work with Data Engineering to shape data platform capabilities, optimize pipeline performance, and ensure data quality through comprehensive testing frameworks - Champion Best Practices: Establish standards for dbt development, documentation, testing, and deployment that scale as Vanta's data needs grow How to be successful in this role: - Experience: At least 4 years in Analytics Engineering, Data Engineering, or equivalent roles focused on transforming and modeling data for analytics. Strong preference for candidates with 2+ years of deep dbt experience architecting projects, not just writing models. - dbt Expertise: Advanced proficiency with dbt (dbt Cloud preferred)—you've built or significantly contributed to dbt projects, managed configurations, implemented testing frameworks, and established governance patterns. - Data Modeling: Strong dimensional modeling skills (facts, dimensions, star schemas, data marts) and experience designing scalable analytical data architectures in modern cloud warehouses (Snowflake, BigQuery, Redshift). - GTM/Revenue Metrics: Solid understanding of go-to-market and financial metrics such as ARR, NRR, GRR, ACV, pipeline coverage, conversion rates, and quota attainment. Ability to translate business definitions into technical models. - SQL Mastery: Advanced SQL skills for complex transformations, aggregations, window functions, and performance optimization over large-scale datasets. - Collaboration: Proven ability to work effectively with cross-functional partners, including business analysts, finance teams, data engineers, and business stakeholders. You can translate technical concepts for non-technical audiences and vice versa. - Data Quality Mindset: Obsessed with correctness - you proactively implement testing ... (truncated, view full listing at source)