Analytics Engineer, GTM

Analytics Engineer supporting Go-to-Market teams by building scalable data models, metrics, pipelines, visualizations, and self-service products. The role requires 10+ years of data experience, deep SQL expertise, Python proficiency, and strong business judgment.

About the job

Responsibilities

Partner with Go-to-Market teams to identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions.
Define, source, validate, and operationalize business metrics for planning and daily decision-making.
Lead cross-functional data projects and establish data strategy for new business domains.
Build scalable data models and ETL pipelines integrating and transforming multiple data sources into trusted datasets.
Create dashboards, reports, analytical tools, and self-service data products.
Own metrics, analytical models, and data products from exploration and prototyping through production and maintenance.
Select appropriate approaches across analysis, modeling, visualization, and self-service tooling based on audience, urgency, complexity, and value.
Prioritize competing requests while balancing immediate needs with long-term data quality and scalability.
Use AI-assisted development tools while maintaining tested, maintainable code, data models, and documentation.
Communicate complex findings through presentations, written memos, dashboards, and audience-appropriate formats.

Requirements

10+ years of experience in a relevant data role within fast-moving, results-oriented organizations.
Ability to independently structure and own ambiguous, high-impact business problems through recommendation and execution.
High autonomy, resourcefulness, creativity, and sound judgment in technical, operational, and stakeholder contexts.
Deep SQL expertise and extensive experience with large datasets and ETL workflow design.
Understanding of software and analytics engineering practices.
Proficiency in a quantitative programming language, preferably Python.
Experience with business intelligence tools such as Tableau or Looker and self-service analytics.
Experience with custom visualization frameworks such as React, Streamlit, or Plotly Dash.
Ability to turn complex analysis into persuasive narratives.
Exceptional attention to detail and commitment to accuracy.
Demonstrated business impact, ideally in Sales, Finance, Support, or another Go-to-Market function.