Senior Ai/Ml Engineer - Aws & Mlops Lead (Remote)

Futureproofing; Quilmes; Teletrabalho; ARS 181 747 000 - 272 620 000; Tempo integral

Resumo da oferta

Futureproofing is seeking a Senior Data and AI Cloud Solution expert to partner with customers and internal teams to design and deploy scalable Oracle Cloud architectures. The role focuses on data platforms, data lakehouse strategies, and analytics-driven outcomes in production environments.

You will lead discussions, craft end-to-end data pipelines, and help customers adopt OCI and multicloud strategies across on-prem and cloud ecosystems. 8+ years of experience is required.

Qualificações

• 8+ years of experience in data engineering, data architecture, or related roles.
• Hands-on experience designing enterprise data platforms that scale and operate reliably in production.
• Practical knowledge of distributed processing, data integration, and modern analytics architectures.
• Experience with Spark, Databricks, Snowflake, BigQuery, or cloud data services.

Responsabilidades

• Partner with customers, sales, engineering and product teams to design, demonstrate and deploy Oracle Cloud architectures addressing business problems.
• Design data platforms for integration, storage, processing and analytics.
• Recommend data lake, lakehouse, or data warehouse approaches per customer needs.
• Design batch and real-time pipelines (ETL/ELT) and cross-platform integration.
• Lead architecture trade-offs on security, governance, performance, scalability, resilience, and cost.
• Build data foundations for analytics, ML, and generative AI use cases when relevant.

Conhecimentos

Data engineering

Data architecture

Cloud services

Customer engagement

Distributed processing

Communication

Multicloud

Ferramentas

Spark

Databricks

Snowflake

BigQuery

OCI

Descrição da oferta de emprego

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.