HOURGLASS COSMETICS — Data Analyst (Hybrid)
Connected by creativity and driven by purpose. Hourglass Cosmetics is a vegan and cruelty-free beauty brand, redefining luxury cosmetics with high-performance products, innovative formulas, and award-winning franchises. Recognized by Forbes, Fast Company and Time Magazine as one of the most inventive beauty companies, Hourglass leads the industry with its breakthrough products and its commitment to animal welfare. Founded in 2004, Hourglass is globally available in 32 markets and over 4,600 doors including Sephora, Ulta, Neiman Marcus, Selfridges, Space NK and more. Hourglass became part of the Unilever Prestige division in 2017. Discover more about the Hourglass brand story and mission on our website hourglasscosmetics.com
We are seeking a Data Analyst to improve data quality, structure, and analytical processes across the organization. This role is central to enabling reliable reporting and better decision-making — particularly in support of finance, demand planning, commercial teams, and cross-functional operations.
This person will own how data flows between systems, identify gaps and inefficiencies, and build scalable datasets and reporting infrastructure. As Hourglass continues to grow, the accuracy and integrity of our data is foundational to how we plan, allocate resources, and serve our retail and DTC channels effectively.
In the first 90 days, this person will have developed a clear understanding of Hourglass’s data landscape, identified the most critical data quality gaps, and established themselves as a trusted partner to Finance, Demand Planning, Commercial Sales, and IT. Within six months, they will have improved the reliability of key reporting outputs and begun systematically automating and documenting recurring processes.
WHAT YOU DO:
- Identify and resolve data quality issues, inconsistencies, and manual inefficiencies across the organization.
- Build and maintain clean, well-structured data tables used for reporting and downstream analysis.
- Own and evolve the Power BI environment, including data models, dashboards, and reports used by leadership and cross-functional teams.
- Support demand planning and commercial finance functions by building and maintaining reliable datasets for forecasting, sell-through analysis, and inventory reporting.
- Review and understand existing data sources, structures, and workflows across systems, including ERP and retail planning platforms.
- Automate and optimize recurring data and reporting processes, identifying opportunities to streamline and scale operations.
- Perform validation, reconciliation, and root-cause analysis when data issues arise, ensuring accuracy and consistency across sources.
- Enhance and