About the role

Responsibilities

You will play a key role in supporting the area's data-driven culture, being responsible for giving our customers a voice through data.
You will work from data collection and processing to creating dashboards and reports that monitor the main CX metrics (NPS, CSAT, CES).
Your work will provide the evidence needed for the CX and Operations teams to make strategic decisions that ensure customer satisfaction and loyalty.
Collect, clean and process data from various sources related to the customer journey and the company's operations, ensuring data quality, integrity and consistency for analysis.
Analyze and cross-reference data daily within the Voice of the Customer Program and CX projects.
Monitor NPS (Net Promoter Score), the company's main metric, daily, and other drivers such as CES/CSAT, as well as their trigger data and accuracy.
Cross-reference operational indicators with CX metrics.
Contribute to the design, review and maintenance of recurring and ad hoc survey distributions.
Create and maintain dashboards and reports that turn complex data into actionable insights for the CX team and for store, logistics and back office operations.
Collaborate with multidisciplinary teams such as technology, data, commercial, operations, process and design in the analysis and monitoring of customer data across the company.
Document processes, metric definitions, analytical criteria and deliverables.
Produce presentations with clear, data-driven storytelling.
Monitor and respond to area tickets.

Bachelor's degree in a quantitative field (Statistics, Mathematics, Data Science, Engineering, Computer Science or related disciplines).
Strong analytical skills, with the ability to process, consolidate and interpret data for decision-making.
Knowledge of SQL for data manipulation.
Advanced Excel for quick analyses (pivot tables, VLOOKUP, etc.).
Experience with Power BI/Tableau or other data visualization tools.
Methodological knowledge of data modeling — how databases work (dimensions, filter context, row context, calendar tables, and how different data tables relate).
ETL knowledge to extract, transform and load data, performing full data cleaning to ensure 100% accuracy and trust in the dataset before analysis.
Ability to work in agile, dynamic environments and adapt quickly to change.
Preferred qualifications:
Knowledge of data visualization best practices.
Familiarity with CX metrics (NPS, CES, CSAT, etc.).
Experience with NPS programs and CX platforms such as Qualtrics or Medallia.
Knowledge of Databricks (creating notebooks, queries/views, etc.).
Basic to intermediate Python: ability to perform small data analyses, task automation and ETL.
Knowledge of predictive modeling to forecast risks.