Business Intelligence Developer (english)

Google Google · Big Tech · Mexico City, CDMX, Mexico

This role focuses on Business Intelligence for Google Cloud Finance, involving data modeling, pipeline development, and dashboard creation. While it mentions applied data science, building models, and statistical/ML techniques, the core function is BI and financial reporting infrastructure, not the direct development or deployment of AI/ML models as a primary deliverable. The role aims to enable decision-making through data analysis and automation within a financial context.

What you'd actually do

  1. Own the design, development, and maintenance of critical data assets for Cloud Finance, including data marts, pipelines, and dashboards, while building an insightful, accurate, and production-level financial reporting infrastructure.
  2. Build anomaly detection, drill-down, forecasting, and what-if modeling solutions, applying problem-solving acumen alongside technology to surface analytics and insights at scale.
  3. Identify opportunities to improve financial operations by devising new and automating financial models and processes, statistical or driver-based forecasts and simulations.
  4. Act as a trusted and reliable partner to finance colleagues across Google.

Skills

Required

  • data modeling
  • developing data sets
  • creating data visualizations
  • Looker or Tableau
  • SQL queries
  • English fluency

Nice to have

  • MBA, Master's degree, or advanced degree in a Technical or Scientific field of study
  • data-driven sales operations
  • consulting
  • program management
  • cross-functional BI initiatives in a cloud business
  • Python
  • Go
  • JavaScript
  • HTML
  • cloud-based data platforms
  • related BI services
  • statistical modeling
  • machine learning
  • data mining techniques
  • communicate technical concepts to both technical and non-technical audiences

What the JD emphasized

  • applied data science
  • automation opportunities
  • building models
  • statistical and data engineering skills
  • anomaly detection
  • forecasting
  • what-if modeling
  • automating financial models and processes
  • statistical or driver-based forecasts and simulations
  • machine learning
  • data mining techniques