- Company Name
- Jungle Scout
- Job Title
- GTM Engineer
- Job Description
-
**Job Title:** GTM Engineer
**Role Summary:**
Drive the accuracy, scalability, and continuous improvement of Amazon competitive intelligence tools by integrating data engineering, model validation, and go‑to‑market strategy. Collaborate across Revenue Operations, Data, Marketing, and Sales to ensure analytical and AI outputs reliably support revenue decisions.
**Expectations:**
- Own end‑to‑end quality control for segmentation, forecasting, attribution, and AI models.
- Translate business strategy into measurable, data‑driven solutions.
- Maintain and enhance data infrastructure that powers GTM analytics.
- Adapt to evolving business priorities and evolving model requirements.
**Key Responsibilities:**
- Design and execute structured output review processes; conduct systematic audits on models and insights.
- Build feedback loops for model retraining; set quality benchmarks and monitoring dashboards.
- Partner with Data and Product teams to refine training datasets, reduce bias, and mitigate drift.
- Write and optimize complex SQL queries; manage relational databases and data warehouse schemas.
- Construct scalable data models and ETL pipelines; implement QA checks across data transformations.
- Integrate CRM, marketing automation, billing, and product analytics tools for seamless interoperability.
- Translate business goals into GTM analytics (territory planning, lead scoring, segmentation, pipeline forecasting).
- Develop reporting frameworks that inform strategic decisions and align with evolving objectives.
**Required Skills:**
*Technical*
- Advanced SQL (complex joins, window functions, aggregations, query optimization).
- Deep knowledge of relational databases, data warehousing, and data modeling.
- Experience with ETL processes and data pipeline design.
- Familiarity with CRM and marketing automation platforms (Salesforce, HubSpot, Marketo, etc.).
- Proficiency in BI tools (Looker, Tableau, Sigma, etc.).
- Exposure to model validation, performance monitoring, or AI/ML quality frameworks.
*GTM & Business Acumen*
- Strong understanding of SaaS go‑to‑market processes across Marketing, Sales, and Customer Success.
- Experience with pipeline analytics, revenue forecasting, attribution, and SaaS metrics (ARR, CAC, LTV, churn, conversion rates, pipeline coverage).
- Ability to link model outputs to business impact and strategic objectives.
*Quality & Analytical Mindset*
- Detail‑oriented with a commitment to data integrity.
- Skilled at designing QA processes and review frameworks.
- Capability to detect anomalies, inconsistencies, and model drift.
- Systems thinker balancing automation and oversight.
*Nice to Have*
- B2B SaaS or eCommerce background.
- Python or scripting for automation and validation.
- Experience with product usage data and experimentation frameworks (A/B testing, cohort analysis).
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Data Analytics, Business Analytics, or related field.
- 3+ years of relevant experience in data engineering, model validation, or GTM analytics.
- Relevant certifications (e.g., Google Data Analytics, Microsoft Certified: Data Analyst Associate, Salesforce Certified Administrator) are a plus but not mandatory.