Lead Backend Data Engineer: Scalable Java & Data Pipelines

Blend; Buenos Aires; Híbrido; ARS 181.190.000 - 271.784.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

AWS Certifications

Databricks

Snowflake

Udemy Business

English lessons

Travel opportunities

Mentoring programs

Company-provided equipment

Descripción de la vacante

Blend is seeking a Lead Backend Data Engineer to design and build scalable data-intensive backend systems using Java. You will lead distributed architectures, optimize concurrency, and ensure reliability at scale with Kubernetes, SQL databases, and modern Java frameworks.

Strong collaboration, mentoring, and improving observability are essential as you partner with cross-functional teams. You will work across large data pipelines, implement production-grade services, and drive performance

Formación

• Deep proficiency in Java with strong understanding of advanced language features and best practices.
• Solid expertise in concurrency patterns, multi-threading, thread synchronization (locks, barriers, mutexes), atomic operations, and volatile semantics.
• Proven hands-on experience designing and implementing distributed systems, including challenges like consistency, fault tolerance, and data replication.
• Practical knowledge of Kubernetes for container orchestration, deployment strategies, and service management (production-level exposure expected).
• Strong SQL and database design fundamentals.
• Experience with system profiling, performance analysis, and optimization techniques.
• Familiarity with monitoring and observability tools such as Grafana, Prometheus, or Loki.
• Excellent problem-solving skills and ability to debug complex, distributed system issues.
• Strong communication skills and ability to mentor and collaborate with team members.
• Experience with Spring Framework or other modern Java backend frameworks is a plus.
• Background in Kafka or event-streaming architectures is a plus.
• Familiarity with reactive programming frameworks or reactive systems design is a plus.
• Prior experience in programmatic advertising or real-time data processing systems is a plus.

Responsabilidades

• Design and build scalable backend systems using Java, with deep expertise in production-grade application development.
• Lead the architecture and implementation of distributed systems, ensuring reliability, scalability, and performance across complex multi-service environments handling large-scale data processing.
• Develop and optimize concurrent and multi-threaded applications, implementing thread synchronization patterns, locks, barriers, and atomic operations for high-performance, data-intensive systems.
• Build and maintain big data pipelines and infrastructure to handle high-volume data ingestion, processing, and storage at scale.
• Manage containerized workloads using Kubernetes, defining deployment strategies, scaling policies, and resource management for backend services processing big data workloads.
• Collaborate with cross-functional teams to define service contracts, APIs, and integration patterns.
• Implement observability and monitoring solutions to ensure system health and performance visibility.
• Support production deployments, troubleshoot complex issues, and drive continuous improvement initiatives.

Conocimientos

Java backend

Concurrency / multi-threading

Distributed systems design

Problem solving

Mentoring & collaboration

English communication

Reactive programming

SQL / database design

Spring Framework

Kafka / event streaming

Herramientas

Kubernetes

Grafana

Prometheus

Loki

Spring Framework

Kafka

Descripción del empleo

Blend is seeking a Lead Backend Data Engineer to design and build scalable data-intensive backend systems using Java. You will lead distributed architectures, optimize concurrency, and ensure reliability at scale with Kubernetes, SQL databases, and modern Java frameworks.

Strong collaboration, mentoring, and improving observability are essential as you partner with cross-functional teams. You will work across large data pipelines, implement production-grade services, and drive performance