• Transforming enterprise business data into insights • Collaborate with business stakeholders to understand their data needs • Analyzing business requirements and translating them into technical specifications • Design, develop and implement data engineering solutions using Azure Databricks Lakehouse platform • Build Data and AI solutions leveraging Databricks components • Conduct detailed data analysis to identify existing data tables, design new tables, views and other objects • Apply AI and machine learning techniques to structured and unstructured data processing • Ensure data quality, integrity, and security throughout the data lifecycle • Collaborate with data scientists and analysts to meet data requirements • Communicate effectively with stakeholders on complex data concepts

• Análisis, diseño y desarrollo de soluciones de ingeniería de datos en entornos cloud. • Construcción y mantenimiento de pipelines de datos. • Tratamiento, integración y análisis de grandes volúmenes de información. • Optimización de procesos de datos en plataformas Microsoft Azure. • Data engineering y data analysis.

• Own and improve data orchestration patterns (Scheduling, Retries, Backfills). • Strengthen deployment and operational patterns to reduce "firefighting" for internal teams. • Ensure data pipelines and models are production-grade and operationally sound. • Use Terraform to support infrastructure-as-code for data platform components. • Document patterns and decisions to ensure internal teams can operate independently.

• Join as a founding engineer on Reporting & Statements team • Design systems for every financial report and statement delivery • Build automated frameworks for accuracy and consistency in financial reporting