• Monitor daily batch processing activities to proactively identify issues. • Troubleshoot batch job errors using SOPs and statistical analysis methods. • Update and maintain SOPs for batch jobs and monitoring workflows. • Identify and recommend improvements to operational processes during release cycles. • Assist with implementing monitoring solutions for new processes. • Maintain clear documentation and strong communication across teams. • Analyze production data using SQL to support issue triage and root‑cause investigation. • Manage assigned tickets and document issues that need conversion to bugs for further review.

• Relevar con los stakeholders sus necesidades y traducirlas en requisitos funcionales claros. • Analizar, comprender, identificar y recopilar los datos que deben ser extraídos de los sistemas transaccionales para requerimientos específicos. • Coordinar con los Data Stewards (custodios de datos de fuentes transaccionales) para comprender e identificar la información que debe ser ingestada al entorno único de datos del país. • Agrupar, ordenar y clasificar los datos recopilados a partir de estructuras existentes o sistemas predeterminados. • Definir los modelamientos de datos a construir o evolucionar sobre el Datalake de Argentina. • Homologar y estandarizar los datos de las diferentes unidades de negocio del país. • Documentar todos los detalles técnicos y requisitos funcionales necesarios para su posterior construcción por parte de los ingenieros de datos. • Colaborar de forma estrecha con los ingenieros de datos para asegurar que los requisitos funcionales sean comprendidos e implementados correctamente. • Participar en revisiones de código y validaciones de datos para velar por la calidad, controlando la integridad y el análisis de descuadre de data (tanto en requerimientos nuevos como existentes).

• Diseñar y desarrollar dashboards en Power BI para usuarios de negocio. • Construir métricas, KPIs y modelos analíticos utilizando DAX. • Desarrollar consultas SQL en Amazon Athena para análisis y generación de datasets. • Traducir requerimientos de negocio en soluciones analíticas claras y accionables. • Validar calidad de datos y optimizar performance de modelos y visualizaciones.

• Design, run, and analyse A/B tests and other experiments across the customer lifecycle; from acquisition and conversion through to retention and reactivation. • Build cohort, funnel, and retention analyses that uncover what's driving customer behaviour and where the biggest opportunities sit. • Lead deep-dive investigations into commercial performance, customer churn, fraud patterns, and product engagement. • Translate ambiguous business questions into structured analytical problems, and the answers into clear recommendations. • Present findings to senior stakeholders in a way that's clear, honest, and decision-ready; not just charts, but conclusions. • Build and maintain self-service dashboards and reports that give teams the data they need, when they need it. • Develop a deep understanding of customer acquisition, conversion, retention, commercial performance, and user experience metrics. • Work alongside the Product and Development teams to shape and deliver on the data roadmap. • Partner with Data Engineers on data quality, modelling, and pipeline reliability, also flagging gaps and helping define what "good" looks like. • Support Customer Success, Commercial, Marketing, and Compliance teams with ad hoc analysis and reporting. • Help create and enforce policies around data governance, quality, and responsible use. • Identify opportunities to improve how we collect, model, and surface data across the business. • Stay close to the customer journey and be curious about how people experience our product and what the data says about it. • Champion experimentation as a core part of how we make decisions.