• Desarrollar y mantener **procesos ETL** para la extracción, transformación y carga de datos. • Integrar información proveniente de **SQL Server, DB2 y Oracle** hacia **Data Warehouses corporativos**. • Programar flujos de transformación de datos utilizando **SSIS y Microsoft Fabric**. • Desarrollar y optimizar **scripts y procesos de bases de datos**. • Analizar requerimientos de usuario y apoyar en la definición de **especificaciones técnicas**. • Elaborar y mantener **manuales y documentación técnica**. • Cumplir con las políticas, estándares y lineamientos de la compañía. • Participar activamente como desarrollador/a en **equipos Scrum**, colaborando en ceremonias ágiles. • • Asegurar la **calidad, trazabilidad y mantenibilidad** de las soluciones implementadas.

• Розробка ETL потоків на основі технології Azure Cloud stack: такі як Databricks, Azure Data Factory, Azure Data Lake, HD Insights, SQL DW, аналітика потоків, машинне навчання, R server • Виправлення помилок та оптимізація продуктивності для потоків обробки даних, моделей даних • Створення та підтримка звітів, моделей, панелей моніторингу

- Own **ad-hoc reporting and analysis** for operations, finance, and leadership - Build and maintain **Power BI dashboards and reports** - Translate ambiguous business questions into clear analytical outputs - Partner with stakeholders to define and refine KPIs and metrics - Ensure reporting is accurate, performant, and trusted **SQL & Data Modeling** - Write high-quality SQL to support reporting and analytics - Build and improve **analytics-ready (gold-layer) datasets** - Contribute to dimensional and fact-based data models - Help improve consistency, usability, and documentation of core datasets **Growth & Technical Evolution** - Gradually take on more responsibility in data modeling and analytics engineering - Collaborate on improving analytics architecture and best practices - Explore advanced analytics or ML use cases over time (as interest and readiness allow)

• Drive the implementation and continuous improvement of our data connections, analytics best practices, and ETL processes. • Centralize the Company’s cloud data into Snowflake and facilitate modeling to support data analysis requirements from all functional groups of the company and its clients. • Create a common data framework and glossary so all company and client data can be analyzed in a unified manner. • Work with the product, operations, and executive management teams to create a data- enabled user and client roadmap that clearly defines roles and responsibilities while bringing all teams into our collaborative data programs. • Collaborate with Sales, Marketing and Services leadership to support our external client base needs. • Create and execute a plan to develop and mature our ability to measure and optimize usage growth, aligned with our user and client roadmap. • Ensure all transactional systems can communicate with our modern data tech stack and that production data adheres to a unified data model. • Collaborate with all functions of the company to address data needs and make required data available to analysts and end-users. • Build a multi-modal service model that meets the non-homogeneous needs of our functional groups, from full service to self service, across our data stack.