Staff Business Intelligence Engineer
Role Description
We're looking for a Staff Business Intelligence Engineer to partner with engineering and product teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.
Responsibilities
Partner Strategically: Collaborate with Data Science, Product, Marketing, Sales, and Engineering teams to understand their goals and challenges. Your work will directly influence decision-making across the organization.
Build Solutions: Design, develop, and maintain reliable data pipelines and models that turn raw data into meaningful insights. Your work will simplify complex concepts into user-friendly dashboards and visualizations.
Drive Impact: Identify trends, diagnose problems, and craft solutions using metrics, reporting tools, and predictive models.
Ensure Quality: Maintain high standards for data governance, privacy, and security while ensuring data quality and reliability.
Communicate Insights: Translate data into compelling stories, empowering stakeholders at all levels to take action.
Prioritization: Understand what matters most and prioritize ruthlessly
Requirements
Technical Expertise:
Advanced SQL with hands-on experience building and optimizing data pipelines.
Knowledge of data modeling best practices (e.g., dimensional modeling).
Experience with BI tools such as Tableau, Looker, or PowerBI.
Analytical Mindset: Strong problem-solving skills and the ability to identify key trends in complex datasets.
Collaboration Skills: A natural communicator who can translate business needs into technical requirements and technical results into actionable business insights.
Experience:
8-10+ years of experience in data science, data engineering, or a similar field.
Proven track record of delivering data-driven projects that drive meaningful results.
Familiarity with cloud environments like Snowflake or Databricks is a plus.
Education: Bachelor’s degree in a quantitative field like Computer Science, Engineering, Math, Statistics, or Economics. Master’s degree is a plus.
Preferred Qualifications
Master’s or Ph.D. Degree in a quantitative field
Experience with predictive modeling, Machine Learning, and A/B Testing methods
Compensation
US Zone 1
$219,300—$296,700 USD
US Zone 2
$197,400—$267,000 USD
US Zone 3
$175,400—$237,400 USD
About the job
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Staff Business Intelligence Engineer
Role Description
We're looking for a Staff Business Intelligence Engineer to partner with engineering and product teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.
Responsibilities
Partner Strategically: Collaborate with Data Science, Product, Marketing, Sales, and Engineering teams to understand their goals and challenges. Your work will directly influence decision-making across the organization.
Build Solutions: Design, develop, and maintain reliable data pipelines and models that turn raw data into meaningful insights. Your work will simplify complex concepts into user-friendly dashboards and visualizations.
Drive Impact: Identify trends, diagnose problems, and craft solutions using metrics, reporting tools, and predictive models.
Ensure Quality: Maintain high standards for data governance, privacy, and security while ensuring data quality and reliability.
Communicate Insights: Translate data into compelling stories, empowering stakeholders at all levels to take action.
Prioritization: Understand what matters most and prioritize ruthlessly
Requirements
Technical Expertise:
Advanced SQL with hands-on experience building and optimizing data pipelines.
Knowledge of data modeling best practices (e.g., dimensional modeling).
Experience with BI tools such as Tableau, Looker, or PowerBI.
Analytical Mindset: Strong problem-solving skills and the ability to identify key trends in complex datasets.
Collaboration Skills: A natural communicator who can translate business needs into technical requirements and technical results into actionable business insights.
Experience:
8-10+ years of experience in data science, data engineering, or a similar field.
Proven track record of delivering data-driven projects that drive meaningful results.
Familiarity with cloud environments like Snowflake or Databricks is a plus.
Education: Bachelor’s degree in a quantitative field like Computer Science, Engineering, Math, Statistics, or Economics. Master’s degree is a plus.
Preferred Qualifications
Master’s or Ph.D. Degree in a quantitative field
Experience with predictive modeling, Machine Learning, and A/B Testing methods
Compensation
US Zone 1
$219,300—$296,700 USD
US Zone 2
$197,400—$267,000 USD
US Zone 3
$175,400—$237,400 USD