Lead Data Engineer for Automated BI & Predictive Analytics

Blend; Municipio de Esquel; Presencial; ARS 1.500.000 - 2.300.000; Jornada completa

Descripción de la vacante

Blend is seeking a Data Engineer Lead to design, develop, and support data solutions that enable reporting, business intelligence, and predictive analytics across the organization.

You will automate recurring reports, convert Excel workbooks into automated data pipelines, optimize SQL queries and data models, and support production data preparation and model scoring using Python, Databricks, and Tableau.

Formación

• Experience designing, automating, and delivering production reporting and analytics solutions.
• Strong SQL Server development and database management skills for production reporting workloads.
• Proficiency in Python for automation and data processing; experience with Databricks.
• Demonstrated BI report/dashboard development using Tableau or similar tools.

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 Server

Python

Databricks

Tableau

BI Development

Data Modeling

Automation

Production Reporting

Stakeholder Communication

Herramientas

Databricks

Tableau

Power BI

Descripción del empleo

Blend is seeking a Data Engineer Lead to design, develop, and support data solutions that enable reporting, business intelligence, and predictive analytics across the organization.

You will automate recurring reports, convert Excel workbooks into automated data pipelines, optimize SQL queries and data models, and support production data preparation and model scoring using Python, Databricks, and Tableau.