• Reporting to the Data Platform Lead, you will be a hands-on senior engineer responsible for building and maintaining ApprovalMax's enterprise data platform. • Own the design and delivery of production-grade data pipelines, drive engineering quality across the data stack, and act as a technical mentor for the broader analytics team. • Design, build, and maintain scalable ELT pipelines, ingestion processes, and transformation layers. • Write production-grade Python for orchestration, custom ingestion, and data transformation logic. • Investigate and resolve pipeline failures within agreed SLAs; lead root-cause analysis and implement durable fixes. • Implement and maintain data quality frameworks across the platform; ensure critical data assets have explicit quality contracts. • Partner with Product Engineering, RevOps, and Finance to define and maintain data contracts.

• Diseñar, desarrollar y mantener soluciones de integración y procesamiento de datos en el ecosistema Azure. • Asegurar la disponibilidad, calidad y trazabilidad de la información mediante la construcción y orquestación de pipelines de datos escalables. • Orquestar procesos de integración de datos desde múltiples fuentes, incluyendo bases de datos relacionales, sistemas on-premise, APIs y servicios cloud. • Configurar y administrar Linked Services, Integration Runtime y Self-hosted Integration Runtime. • Implementar procesos de transformación y preparación de datos mediante Mapping Data Flows. • Gestionar la carga y almacenamiento de datos en Azure Data Lake Storage Gen2, Azure Blob Storage, Azure SQL Database y Azure Synapse Analytics. • Desarrollar consultas y procesos de transformación utilizando SQL y Python. • Implementar mecanismos de control de versiones y despliegue continuo mediante Git y Azure DevOps. • Aplicar buenas prácticas de seguridad, gobernanza y acceso a datos utilizando Key Vault, Managed Identities y RBAC. • Monitorear y optimizar el rendimiento de los procesos de integración y carga de datos. • Documentar desarrollos, flujos de integración y procedimientos operativos asociados a las soluciones implementadas.

• Design, build, and maintain ELT/ETL pipelines that move data reliably from source systems into a cloud data warehouse environment. • Write clean, performant, and well-documented SQL to transform raw data into analyst-ready models and reporting layers. • Develop and maintain Power BI dashboards and reports that give business stakeholders clear, trusted views of company performance. • Apply best practices in data modeling within Power BI (star schemas, DAX measures, performance optimization). • Actively use AI tools (such as LLM assistants, copilots, and agentic workflows) to accelerate development and improve code quality. • Engage directly with business stakeholders to understand data needs in context.

• Data Pipeline Support: Assist in building and maintaining scalable ETL/ELT pipelines using AWS Glue, PySpark, and cloud-native services. • BI Reporting & Visualization: Develop and maintain interactive dashboards and reports using Power BI to visualize cloud cost, performance, and operational metrics for stakeholders. • AI/ML Assistance: Support the development and testing of AI agents and machine learning models designed to monitor cloud resource health. • Data Management: Help manage data storage, processing, and query performance using the Snowflake cloud data platform and AWS Athena. • Workflow Orchestration: Learn to orchestrate and monitor data workflows using Apache Airflow DAGs. • Automation: Assist in automating operational workflows using Python and intelligent scripting. • Collaboration: Participate in code reviews, team design sessions, and Agile ceremonies to learn best practices and contribute to team goals. • Documentation: Maintain clear documentation for data processes and assist in tracking project progress via tools like Jira.