Lead Product Performance Data Analyst, Global

Join Vantage as a Product Performance Data Analyst to build and govern the data foundation that drives our product infrastructure platform. You’ll shape the integrated cost, schedule, and benchmark data for global data centers and enable decision making across product, engineering, procurement, and operations. You work hands-on to create repeatable, auditable data processes and dashboards that reveal performance insights and support product optimization at scale. This role blends advanced data management, analytics, and industry benchmarks to transform how Vantage measures and improves its offerings.

• above market total compensation package
• comprehensive health and welfare benefits
• retirement plan
• paid leave benefits
• training and development opportunities
• recognition programs

• Define and maintain KPIs and analytics views for leadership to evaluate product performance
• Maintain WBS, cost, schedule hierarchies, schemas, data dictionaries, and reference data
• Validate submissions against required fields and standards; ensure data quality through QA checks
• Build and automate data validation, reporting, and import routines with developers and IT
• Create Power BI dashboards and analytical views across baseline and reference points
• Support variance analysis by maintaining comparable baseline/reference data and flagging inconsistencies
• Capture lessons from validated outcomes to fed back into the governed data foundation
• Maintain regional factor-pack inputs and support configuration bridge analysis and regional variant data maintenance
• Maintain change logs, assumptions logs, validation reports, and refresh-cycle records
• Translate dataset requirements into tooling specifications and assist automation of validation and reporting

• 4–7 years of experience in data analysis, analytics engineering, data management, or related fields
• Strong SQL, Power Query/Power BI, data modeling, validation, and controlled data maintenance
• Experience structuring, validating, reconciling, and documenting complex datasets
• Solid understanding of data modeling concepts, schemas, reference data, hierarchy, and lineage
• Experience with maintaining controlled data structures including mappings and hierarchies
• Experience building repeatable data quality and validation regimes (QA checks, reconciliation, audit logs)
• Strong communication and documentation skills for explaining assumptions and confidence levels

• strong communication
• documentation discipline
• data-driven decision making
• Excel, Power Query, SQL
• Power BI or equivalent BI tool
• Databricks