Data Engineering Manager, Databricks & KPI Lead

Blend; Bogotá; Presencial; COP 180.000.000 - 280.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

At-home medical assistance

Private healthcare

Christmas kit

Graduation day off

Family Day

Savings incentive program

Education loan support

Descripción de la vacante

Blend is seeking a Data Engineering Manager to lead the next growth phase, shaping semantic layers, KPI models, and data pipelines for enterprise AI and analytics.

You will collaborate with business owners, BI Analysts, and AI Engineers to translate KPI requirements into scalable data architectures, ensure data quality, security, and governance, and drive production readiness across multi-market datasets.

Formación

• 7+ years of experience in Data Engineering and KPI/metric modeling.
• Advanced proficiency in SQL and Python for data processing and pipelines.
• Cloud data platforms knowledge, esp. Azure Databricks and ELT/ETL tooling.
• Experience in data modeling, conformed dimensions, and multi-source integration.
• Profiling data quality, lineage, and reconciliation across enterprise sources.
• Ability to work with business stakeholders to gather KPI requirements.

Responsabilidades

• Design, build, and maintain semantic layers and KPI models using Databricks Metric Views.
• Translate KPI requirements into reusable data models and logic.
• Profile data quality, lineage, and reconciliation across source systems.
• Design and implement data pipelines for AI-generated narratives and analytics.
• Define conformed dimensions and multi-market data variations for reporting.
• Collaborate with BI Analysts and AI Engineers to align KPI definitions with data structures.
• Establish data quality, validation, and monitoring frameworks.

Conocimientos

Databricks Metric Views

SQL

Python

Azure Databricks

Data modeling

ETL/ELT tooling

Git

Herramientas

Databricks

Git

Descripción del empleo

Blend is seeking a Data Engineering Manager to lead the next growth phase, shaping semantic layers, KPI models, and data pipelines for enterprise AI and analytics.

You will collaborate with business owners, BI Analysts, and AI Engineers to translate KPI requirements into scalable data architectures, ensure data quality, security, and governance, and drive production readiness across multi-market datasets.