Senior .Net Engineer — Ai-Native Saas, Remote Latam

Nimble; Buenos Aires; Remote; ARS 400,000 - 700,000; Full time

Job summary

Nimble seeks a Senior Data and AI Cloud Solution professional to partner with customers, sales, engineering and product teams to design, demonstrate and deploy data cloud architectures that address customer business problems using Oracle Cloud.

You will lead technical discussions, design data platforms, pipelines and analytics solutions, and help customers adopt OCI and multicloud architectures, ensuring reliable production readiness and measurable business outcomes.

Qualifications

• 8+ years of experience in data engineering, data architecture, or related roles.
• Experience designing enterprise data platforms that scale, recover from failures, and run reliably in production.
• Distributed processing, data integration, and modern analytics architectures familiarity.
• Experience with Spark, Databricks, Snowflake, BigQuery or cloud data services.
• Ability to connect architecture decisions to business outcomes and explain trade-offs to stakeholders.

Responsibilities

• Discover customers' data challenges, priorities, growth expectations, and success criteria.
• Design data platforms for integration, storage, processing, and analytics.
• Recommend data lake, lakehouse, or data warehouse approaches based on needs.
• Design batch and real-time pipelines, ETL/ELT, and platform integration.
• Assess security, data governance, performance, scalability, resilience, and cost trade-offs.
• Ensure reliable operation with monitoring, failure recovery, and production readiness.
• Lead technical discussions, demos, and proofs of concept with customers.

Skills

Data engineering

Data architecture

Cloud architectures

Client communication

Multicloud

Tools

Spark

Databricks

Snowflake

BigQuery

OCI

Job description

Senior Data and Artificial Intelligence - Cloud Solution

Partners with customers, sales, engineering and product teams to design, demonstrate and deploy Oracle Cloud architectures that address customer business problems. Drives Oracle Cloud customer consumption by accelerating the adoption of Oracle cloud services including discovery, design and deployment.

What you’ll do

• Discover customer's data challenges, priorities, growth expectations, and success criteria.
• Design data platforms for integration, storage, processing, and analytics.
• Recommend data lake, lakehouse, or data warehouse approaches based on each customer’s needs and existing environment.
• Design batch and real-time pipelines, including ETL/ELT and integration across platforms.
• Help customers make informed architecture trade-offs across security, data governance, performance, scalability, resilience, operational needs, and cost.
• Design for reliable operation, including monitoring, failure recovery, and the ability to adapt as demand grows.
• Lead technical discussions, demonstrations, and proofs of concept, and help customers bring validated solutions into production.
• Work with customer and internal teams to resolve integration and operational challenges and support long‑term adoption.
• Build the data foundation for analytics, machine learning, and generative AI use cases when relevant.

What we’re looking for

• 8+ years of experience in data engineering, data architecture, or related roles, including hands‑on experience designing enterprise data platforms that scale with demand, recover from failures, and operate reliably in production.
• Practical knowledge of distributed processing, data integration, and modern analytics architectures.
• Experience with technologies such as Spark, Databricks, Snowflake, BigQuery, or cloud data services.
• The ability to connect architecture decisions to business outcomes and explain trade-offs to different audiences.
• Experience working directly with customers from discovery through delivery.
• Experience with OCI and multicloud architectures is a plus.

If you enjoy understanding what customers need, navigating complex data environments, and helping teams put reliable solutions into production, we’d like to hear from you.

Qué harás

• Comprender los desafíos de datos de cada cliente, sus prioridades de negocio, planes de crecimiento y criterios de éxito.
• Diseñar plataformas para integración, almacenamiento, procesamiento y análisis de datos, eligiendo arquitecturas de data lake, lakehouse o data warehouse según cada caso.
• Diseñar pipelines batch y en tiempo real, incluyendo ETL/ELT e integración entre plataformas.
• Orientar decisiones de arquitectura considerando seguridad, gobierno de datos, rendimiento, escalabilidad, resiliencia, operación y costos.
• Diseñar soluciones preparadas para operar de forma confiable en producción, con monitoreo, recuperación ante fallas y capacidad de adaptación a nuevas demandas.
• Liderar conversaciones técnicas, demostraciones y pruebas de concepto, y ayudar a llevar soluciones validadas a producción.
• Trabajar con equipos del cliente y de Oracle para resolver desafíos de integración y operación e impulsar la adopción sostenida de Oracle Cloud Infrastructure (OCI).
• Establecer la base de datos necesaria para casos de analytics, machine learning e IA generativa cuando corresponda.

Qué buscamos

• Más de 8 años de experiencia en ingeniería de datos, arquitectura de datos o funciones relacionadas, incluyendo experiencia práctica en el diseño de plataformas empresariales.
• Experiencia con plataformas que escalan, se recuperan de fallas y operan de manera confiable en producción.
• Conocimiento práctico de procesamiento distribuido, integración de datos y arquitecturas modernas de analytics.
• Experiencia con tecnologías como Spark, Databricks, Snowflake, BigQuery o servicios de datos en la nube.
• Capacidad para relacionar decisiones de arquitectura con resultados de negocio y explicar sus ventajas y compromisos a diferentes públicos.
• Experiencia trabajando directamente con clientes, desde el descubrimiento de necesidades hasta la entrega de soluciones.
• Se valorará la experiencia con OCI y arquitecturas multicloud.

Si te interesa comprender las necesidades de los clientes, trabajar en entornos de datos complejos y ayudar a los equipos a llevar soluciones confiables a producción, nos gustaría conocerte.