Analytics Engineer
Build data models, analyses, forecasts, automated dashboards, and AI-augmented analytics products for Finance and go-to-market operations. The role requires 2–4 years of analytical or analytics engineering experience, strong SQL and Python skills, and a quantitative degree.
About the job
Responsibilities
- Partner with Finance and go-to-market operations stakeholders to translate business questions into structured analyses and recommendations.
- Build narratives, visualizations, KPIs, performance metrics, and analytical priorities.
- Develop and maintain data and financial models, forecasting logic, and scenario analyses.
- Apply statistical methods and predictive modeling to identify trends, risks, and opportunities.
- Build scalable automated dashboards and self-service data products.
- Write clean, reproducible, version-controlled SQL and Python code.
- Use LLM assistants, coding copilots, AI agents, and workflow automation to improve analytics workflows.
- Maintain data quality, consistency, and governance.
- Collaborate with Finance, adoption, GTM operations, and Data/Tech teams to embed data-driven practices in business processes.
Requirements
- 2–4 years of experience in analytics engineering, data or business analytics, BI development, or a comparable technical and analytical role.
- Strong SQL skills and experience working with large, complex datasets.
- Hands-on Python experience for data analysis, automation, and statistical or predictive modeling.
- Foundations in data modeling or financial modeling, forecasting, and scenario planning.
- Working knowledge of statistical methods and rigorous analytical practices.
- Familiarity with version control, testing, documentation, and BI or data visualization tools.
- Ability to communicate insights clearly to non-technical stakeholders.
- Degree in Computer Science, Engineering, Mathematics, Statistics, Finance, Economics, or a related quantitative field.
- Exposure to modern AI and agentic tools, including LLM assistants, coding copilots such as Cursor, AI agents, and prompt-based automation.
- Exposure to Finance or GTM/revenue operations data.
- Ability to work effectively in a fast-paced, cross-functional environment.
Compensation and Benefits
- Restricted Stock Units and merit-based refresh grants for full-time employees.
- Flexible hybrid work model.
- Paid parental leave, paid time off, learning and mentorship programs, Wellhub memberships, mental health counseling, wellness programs, and paid volunteer time.
Skills
SQL, Python, Statistical Modeling, Predictive Modeling, Data Modeling, Financial Modeling, Forecasting, Scenario Planning, Version Control, Data Visualization, Business Intelligence, Llm Assistants, AI Agents, Cursor
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