Business Intelligence Manager, Product Analytics
New
J
JobgetherProduct Analytics
Fully remote work flexibility, allowing employees to work from a location of their choice within the United States.Full-TimeManager
SalaryCompetitive annual base salary ranging approximately from $94,000 to $158,100 depending on location, experience, and qualifications.
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Job Details
- Experience
- 5+ years
- Required Skills
- SQLBusiness IntelligenceProduct AnalyticsData visualizationStakeholder managementData modeling
Requirements
- Bachelor’s degree in Data Science, Computer Science, Information Systems, Statistics, Mathematics, Business Analytics, or a related field.
- 5+ years of experience in business intelligence, data analytics, product analytics, or a related discipline.
- Proven experience designing and maintaining dashboards, reports, and data models that support cross-functional teams.
- Strong experience with modern BI and data visualization tools.
- Proficiency in SQL or comparable querying languages.
- Experience defining metrics, measurement frameworks, and success indicators.
- Strong analytical skills with the ability to identify patterns and translate findings into recommendations.
- Excellent communication and stakeholder management skills.
- Ability to work independently in a distributed remote environment.
- Strong attention to detail and commitment to data accuracy and quality.
- Experience working with technology, product, marketplace, or operations-focused teams is preferred.
Responsibilities
- Lead the design, development, and optimization of business intelligence dashboards, reports, and analytical tools.
- Define product measurement strategies by identifying success metrics, adoption indicators, and performance benchmarks.
- Translate stakeholder needs into analytical requirements, data definitions, and reporting specifications.
- Build and maintain semantic layers, data models, and queries that support self-service analytics.
- Analyze complex datasets to identify trends, performance drivers, and opportunities.
- Partner with product, operations, finance, and engineering stakeholders to support data-informed decision-making.
- Monitor BI asset quality and investigate data inconsistencies.
- Establish and promote BI best practices, standardized metrics, and scalable analytics processes.
- Provide guidance and training to business users on dashboard interpretation and self-service analytics tools.
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