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Senior Business Intelligence Developer/Analyst
Anaplan
Salford, GBR
Full-time
Mid-Senior
Onsite
Discovered 1 weeks ago
Business intelligence developmentPythonSQLDimensional data modelingSemantic layer designTableau, Power BI, or eazyBI
Free
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Business intelligence developmentPythonSQL
Role Overview
Anaplan is seeking a Senior Business Intelligence Developer/Analyst for engineering reporting and insights within the GPTO Product and Technology department.
The role sits in the Engineering Enablement team and owns high-visibility data domains end-to-end.
The position supports approximately 190 KPIs across delivery, quality, investment, and AI adoption, including measurement of internal AI initiatives.
The role requires turning ambiguous leadership questions into modeled data, semantic layers, and actionable self-service insights.
Key Skills for This Role
Business intelligence developmentPythonSQLDimensional data modelingSemantic layer designTableau, Power BI, or eazyBI
Full Job Posting
Role Overview
Anaplan is seeking a Senior Business Intelligence Developer/Analyst for engineering reporting and insights within the GPTO Product and Technology department.
The role sits in the Engineering Enablement team and owns high-visibility data domains end-to-end.
The position supports approximately 190 KPIs across delivery, quality, investment, and AI adoption, including measurement of internal AI initiatives.
The role requires turning ambiguous leadership questions into modeled data, semantic layers, and actionable self-service insights.
Your Impact
- Own two to three subject areas from raw data to stakeholder presentation, such as executive scorecards, dependency health, investment mix, or DORA performance.
- Design, build, and document semantic layers that simplify data from Jira, GitHub, and other tools for self-service reporting.
- Contribute development tasks and test data to ensure reporting quality and completeness.
- Partner with senior engineering leaders to translate ambiguous questions into defensible data answers.
- Challenge requirements, identify useful metrics, and determine what should and should not be measured.
- Combine traditional metrics and AI telemetry to measure internal AI initiatives.
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