Senior Analytics Engineer (finance)

Whoop Whoop · Consumer · Boston, MA · Business Intelligence & Analytics

Senior Analytics Engineer (Finance) at WHOOP to build and own the data infrastructure for the financial planning model, focusing on data layer design for forecasting, scenario modeling, and reconciliation. This role involves standardizing financial actuals, developing dbt frameworks, and creating Snowflake functions to power the model's logic.

What you'd actually do

  1. build and own the data infrastructure powering WHOOP's financial planning model
  2. design the foundational data layer that enables financial forecasting, scenario modeling, and actuals reconciliation at scale
  3. build the engine that makes analysis possible: standardizing financial actuals in Snowflake, developing reusable dbt frameworks, and creating the Snowflake-native functions and structures that power the model's logic at scale
  4. partner directly with FP&A to translate financial modeling requirements into scalable, tested, and well-documented data products
  5. ensure the system remains reliable and extensible as the business grows

Skills

Required

  • SQL
  • dbt
  • Snowflake
  • financial data concepts
  • data modeling
  • ERP and financial systems
  • Sigma Computing
  • Python
  • Snowpark
  • Snowflake ML functions
  • LLM-based automation
  • AI-augmented finance
  • subscription/SaaS business metrics

Nice to have

  • NetSuite
  • Stripe
  • workbooks
  • input tables
  • materialization
  • calculated columns
  • prompt engineering
  • structured outputs
  • Snowflake Cortex AI functions
  • prior experience building financial models or FP&A systems specifically

What the JD emphasized

  • 4-7 years of experience in analytics engineering, data engineering, or a technical finance/BI role with hands-on ownership of production dbt projects
  • Expert-level SQL
  • Deep dbt experience
  • Strong understanding of financial data concepts
  • Experience designing data models that support parameterized analysis
  • Ability to work autonomously with FP&A stakeholders
  • Experience with Snowflake ML functions
  • Familiarity with LLM-based automation
  • Interest in AI-augmented finance