Finance Analytics Manager (Product & Engineering)
New
United StatesFull-TimeManager
Salary102,000 - 148,000 USD per year
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Job Details
- Experience
- 6–8+ years
- Required Skills
- SQLMicrosoft Power BISnowflakeTableauData visualizationData modelingA/B testingLooker
Requirements
- Bachelor’s degree in Finance, Economics, Data Analytics, Computer Science, or a related field.
- 6–8+ years of experience in FP&A, data analytics, product analytics, or hybrid finance/data roles in high-growth SaaS environments.
- Advanced SQL proficiency with hands-on experience working in data warehouses such as Snowflake.
- Strong experience with BI and visualization tools such as Tableau, Looker, or Power BI.
- Proven ability to design and analyze experiments, including A/B testing and financial impact evaluation.
- Strong analytical mindset with the ability to investigate trends, identify root causes, and translate findings into business insights.
- Experience partnering cross-functionally with technical and non-technical stakeholders.
- Excellent communication, problem-solving, and data storytelling skills.
- Strong attention to detail and ability to manage multiple priorities in a fast-paced environment.
Responsibilities
- Build and own the product finance analytics infrastructure, including scalable data models, reporting systems, and performance tracking frameworks.
- Define, maintain, and govern key product and financial metrics such as ARR, NRR, GRR, retention, and feature adoption.
- Partner with Product and Engineering teams to design, execute, and evaluate product experiments and A/B tests.
- Conduct deep-dive analyses into product and customer behavior trends, translating findings into financial and strategic insights.
- Develop dashboards and reporting tools that provide accurate, timely visibility into product and revenue performance for stakeholders.
- Write, optimize, and maintain complex SQL queries to extract, transform, and structure large datasets for analysis.
- Ensure data integrity, consistency, and governance across all product and finance datasets.
- Drive automation and scalability of analytics processes to improve speed and reliability of insights.
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