Data Engineering Manager: Scale Real-Time Pipelines

Blend; Buenos Aires; Presencial; ARS 133.982.000 - 223.304.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

AWS/Databricks/Snowflake certs

Udemy Business access

English lessons

Flexible working options

Company-provided equipment

Descripción de la vacante

Blend is seeking a Data Engineering Manager to lead end-to-end data pipelines and platform integration for client workflows. You will build and scale a high-performing team, guiding architecture decisions across Snowflake, Databricks, BigQuery, and other platforms.

The role emphasizes production-grade data engineering, performance testing, and strong collaboration with stakeholders. You will own discovery initiatives, design scalable data models, and shape data governance practices while

Formación

• 7+ years hands-on data engineering in production environments.
• 2+ years of direct team leadership or technical management experience.
• Advanced SQL with deep expertise in schema and data-model design, complex joins, and performance optimization.
• Proven track record with high-volume record matching, deduplication, and identity resolution systems.
• Experience with platform-agnostic data engineering—Snowflake, Databricks, BigQuery, Redshift, and similar platforms.
• Demonstrated expertise in pipeline development, performance testing, latency and throughput analysis.
• Experience designing batch and real-time data integration workflows.
• Knowledge of governed clean-room solutions and data governance practices.
• Strong API design, microservices patterns, and event-driven architectures.
• Excellent communication and mentoring abilities.

Responsabilidades

• Design and implement data ingestion architectures on Snowflake.
• Lead data engineering projects end to end—from discovery and requirements through POC validation to production deployment—while building and mentoring a high-performing engineering team
• Design platform-agnostic data pipelines and schemas that scale reliably at high volume, including complex data modeling for submit-grade-return workflows, identity graphs, record matching, and deduplication systems
• Own discovery pipeline initiatives and functional POCs, implementing high-volume matching logic and conducting comprehensive performance, load, and scale testing to validate architectural decisions
• Assess and optimize latency, throughput, connection stability, and integration options including APIs, batch delivery, and governed clean-room workflows
• Define data integration strategies and communicate tradeoffs clearly to clients, guiding infrastructure and tool selection based on performance requirements and business constraints
• Lead partner-facing API design and integration strategy, architecting batch versus real-time decisions and designing governed clean-room solutions for partner data exchange
• Establish technical standards for schema design, SQL quality, pipeline development, and production readiness across the team through reviews, mentoring, and knowledge sharing

Conocimientos

Data pipelines

SQL proficiency

Team leadership

Platform-agnostic design

Snowflake

Databricks

BigQuery

Redshift

Performance testing

API design

Communication

Mentoring

Herramientas

Snowflake

Databricks

BigQuery

Redshift

Descripción del empleo

Blend is seeking a Data Engineering Manager to lead end-to-end data pipelines and platform integration for client workflows. You will build and scale a high-performing team, guiding architecture decisions across Snowflake, Databricks, BigQuery, and other platforms.

The role emphasizes production-grade data engineering, performance testing, and strong collaboration with stakeholders. You will own discovery initiatives, design scalable data models, and shape data governance practices while