Data Engineering Lead: Automate & Scale BI Solutions

Visa Hunt; Chile; Híbrido; CLP 89.280.000 - 167.400.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Certifications in AWS, Databricks, and

Snowflake access

Udemy Business

English lessons

Descripción de la vacante

Blendis seeks a Data Engineer Lead to design, develop, and support data solutions for reporting, BI, and predictive analytics. You will modernize recurring manual reports by converting Excel workbooks and data pulls into automated pipelines and scalable BI systems.

You will also support production model scoring and data preparation to ensure reliable operations. Collaborate with business and technical stakeholders to deliver scalable data solutions, drive best practices, and ensure end-to-end

Formación

• Experience designing, automating, and delivering production reporting and analytics solutions.

Responsabilidades

• Design, develop, and maintain automated data pipelines and analytics solutions.
• Automate manual reporting processes and repetitive data workflows.
• Optimize SQL queries, data models, and processing performance.
• Support production data preparation and model scoring for predictive analytics.
• Monitor data quality, troubleshoot pipeline issues, and improve reliability.
• Collaborate with business and technical stakeholders to deliver scalable data solutions.
• Promote data engineering best practices and drive continuous improvements.

Conocimientos

SQL

Python

Databricks

Tableau

BI Development

Data Modeling

Communication

Herramientas

SQL Server

Looker

Power BI

Tableau

Snowflake

AWS

Descripción del empleo

Blendis seeks a Data Engineer Lead to design, develop, and support data solutions for reporting, BI, and predictive analytics. You will modernize recurring manual reports by converting Excel workbooks and data pulls into automated pipelines and scalable BI systems.

You will also support production model scoring and data preparation to ensure reliable operations. Collaborate with business and technical stakeholders to deliver scalable data solutions, drive best practices, and ensure end-to-end