Data Engineer Lead

We are looking for a Data Engineer to design and build scalable data platforms that enable advanced analytics, forecasting, and customer retention use cases. This role focuses on developing robust data pipelines, integrating complex data sources, and delivering high-quality, model-ready datasets for both BI and AI-driven initiatives.

You will work closely with data, analytics, and business teams to ensure data is reliable, well-structured, and accessible for decision-making, while supporting both operational reporting and advanced modeling use cases.

You may work 100% remotely if you are currently living in LATAM, or you can always join us at the office!

Job Description

• Design, build, and maintain scalable ETL/ELT pipelines using Python and SQL on modern lakehouse architectures.

• Develop data solutions using tools such as Azure Data Factory, Synapse, Fabric, Airflow, or dbt.

• Build and maintain data models and pipelines that support forecasting and customer retention/churn use cases, including feature engineering and reproducibility.

• Integrate data from multiple transactional systems (ERP, CRM, etc.), ensuring proper standardization, entity resolution, and consistency across datasets.

• Implement data quality frameworks, validation processes, and monitoring to ensure reliability and accuracy of data pipelines.

• Design dimensional and semantic data models to support BI and analytics consumption, enabling drill-down capabilities from executive dashboards to detailed views.

• Collaborate with analytics and business teams to support reporting, forecasting, and AI-driven initiatives.

• Ensure data solutions are scalable, performant, and aligned with best practices in data architecture.