What You'll Do
Design and manage reliable data models for critical financial metrics such as annual contract value, recurring revenue, billings, and cost distribution, overseeing their evolution from concept to live production systems. Develop and maintain dbt-based data pipelines with strong governance, ensuring data accuracy and consistent delivery aligned with defined service standards.
Create intuitive, real-time dashboards that support decision-making across revenue analysis, spending oversight, budget comparisons, and forecast reliability. Empower finance teams by reducing dependency on manual reporting, building reusable, self-service datasets in analytics platforms to broaden access to timely insights.
Partner with finance and data teams to define an AI-readable context layer for financial operations, converting accounting principles and business rules into structured formats compatible with large language models. Build tools that allow natural language queries and AI-assisted reporting, enabling non-technical users to explore financial data independently.
Design proactive AI workflows that detect trends, outliers, and meaningful shifts in financial data, delivering timely alerts and insights. Serve as the primary analytics liaison for finance leadership, supporting strategic planning and business growth initiatives through data analysis.
Communicate findings clearly through dashboards, written summaries, and presentations that guide action. Promote adoption of analytics and AI capabilities by training users, resolving issues, and supporting onboarding. Gain deep proficiency in financial data systems, including dbt, Looker, and Omni, becoming the internal authority on finance data infrastructure within the first six months.
Requirements
- Demonstrated interest in AI technologies, including large language models and prompt engineering, with enthusiasm for emerging AI tools
- Proven ability to build and iterate—comfortable prototyping, scripting, and learning new technical skills quickly
- Solid analytical foundation with strong SQL skills and hands-on experience with modern data platforms such as dbt, Databricks, or Snowflake
- High attention to detail, especially when working with financial data that demands precision and correctness
- Excellent written and verbal communication skills, capable of documenting complex logic in ways both people and AI systems can interpret
- Curiosity about business operations, revenue models, and the financial drivers behind organizational decisions
- Ability to operate effectively in uncertain environments, defining clarity and driving projects from initiation through refinement
- Openness to new technologies, evaluating tools based on functionality rather than legacy preferences
Preferred Qualifications
- Experience with AI platforms such as Claude, ChatGPT, or Manus
- 1 to 4 years of professional experience in data, analytics, or related technical roles
Technical Stack
dbt, Looker, Omni, SQL, Databricks, Snowflake, large language models, prompt engineering, AI-powered analytics tooling
Benefits
The company is committed to being an equal opportunity employer, fostering a diverse and inclusive environment where individuals of all backgrounds, experiences, and perspectives can succeed.
