Senior Business Intelligence Engineer
New
J
JobgetherBusiness intelligence
Remote position within the United StatesFull-TimeSenior
SalaryEstimated salary ranges vary by location: $116,960–$146,200 in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont, and Washington D.C.; $123,760–$154,700 in New York, New Jersey, Washington State, and California outside the San Francisco Bay Area; and $137,520–$171,900 in the San Francisco Bay Area.
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Job Details
- Experience
- At least 5 years of professional experience in business intelligence, analytics engineering, data engineering, or a related discipline
- Required Skills
- SQLGitSalesforceTableauCI/CDData modelingdbt
Requirements
- At least 5 years of professional experience in business intelligence, analytics engineering, data engineering, or a related discipline.
- Strong experience with Tableau, particularly for executive reporting and sales analytics.
- Advanced SQL skills and hands-on experience designing and implementing data models.
- Experience defining, documenting, reconciling, and standardizing critical business metrics with cross-functional stakeholders.
- Experience implementing data quality, testing, CI/CD, and data observability frameworks.
- Strong proficiency with Git and CI/CD tools.
- Familiarity with code reviews, automated testing, and development environment separation.
- A bachelor’s or master’s degree in a quantitative field is preferred.
- Experience with Looker/LookML, dbt, Cube.js, or Apache Superset is desirable.
- Experience with AI products and tools such as Claude, Cortex, Glean, or Gemini is a plus.
- Familiarity with Go-to-Market technology stacks such as Salesforce and Gong is preferred.
Responsibilities
- Analyze complex datasets to generate actionable insights and recommendations for revenue operations.
- Develop automated data reconciliation, monitoring, quality checks, and testing frameworks.
- Build data visualizations for technical and business audiences.
- Design and maintain data models for Go-to-Market analytics, reporting, data science, and AI initiatives.
- Apply BI-as-code practices using Git, automated testing, and CI/CD pipelines.
- Partner with Sales, Marketing, Finance, Product, and other teams to translate business needs into analytical solutions.
- Establish, document, and reconcile critical business metrics.
- Identify opportunities to improve data quality, reporting processes, analytics tools, and BI capabilities.
- Share knowledge and mentor colleagues on data practices.
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