Databricks Data Engineering Manager - AI Analytics Leader

Blend; Buenos Aires; Presencial; ARS 208.417.000 - 267.965.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

AWS Certifications

Databricks Training

Snowflake Certification

AI learning paths

Descripción de la vacante

Blend is seeking a Data Engineering Manager to drive semantic layer design, KPI modeling, and scalable data pipelines for AI-enabled analytics. You will partner with business owners, analysts, and AI engineers to translate KPI requirements into robust data architectures, ensuring data quality and governance across enterprise sources.

Required are 7+ years in data engineering, strong Databricks Metric Views experience, and proficiency in SQL/Python.

Formación

• 7+ years in Data Engineering with semantic layer/KPI modeling.
• Hands-on in Databricks Metric Views or equivalent.
• Advanced SQL and Python for processing and pipelines.
• Cloud data platforms experience (Azure Databricks) and ELT/ETL tooling.
• Data modeling, conformed dimensions, Medallion architectures.
• Data quality, lineage, and reconciliation expertise.

Responsabilidades

• Design, build, and maintain semantic layers and KPI models.
• Translate KPI requirements into reusable data models and logic.
• Profile data quality, lineage, and data grain across source systems.
• Develop data pipelines for AI-generated narratives and analytics.
• Define conformed dimensions for multi-market reporting.
• Collaborate with Business Analysts and AI Engineers on KPI definitions.
• Enforce data quality, validation, and monitoring across data assets.
• Implement security, access control, and governance practices.
• Lead technical docs and knowledge transfer at delivery end.
• Support production readiness and deployment to production.

Conocimientos

KPI modeling

SQL

Python

Data governance

Data integration

Stakeholder collaboration

Git

AI/LLM data prep

Herramientas

Databricks Metric Views

Azure Databricks

ETL tooling

Descripción del empleo

Blend is seeking a Data Engineering Manager to drive semantic layer design, KPI modeling, and scalable data pipelines for AI-enabled analytics. You will partner with business owners, analysts, and AI engineers to translate KPI requirements into robust data architectures, ensuring data quality and governance across enterprise sources.

Required are 7+ years in data engineering, strong Databricks Metric Views experience, and proficiency in SQL/Python.