Remote AI-Driven Cloud Data Architect

Bord; Quilmes; Remote; ARS 1,200,000 - 2,000,000; Full time

Job summary

Bord is seeking a Senior Data and AI - Cloud Solution specialist to partner with customers and internal teams to design, deploy and optimize Oracle Cloud architectures for data platforms and AI use cases. You will drive adoption through discovery, design and production implementation in cloud environments.

The role emphasizes hands-on data engineering, architecture decisions, and collaboration with sales, engineering and product teams to deliver scalable data pipelines and analytics solutions.

Qualifications

• 8+ years of experience in data engineering or data architecture.
• Practical knowledge of distributed processing and modern analytics architectures.
• Experience with Spark, Databricks, Snowflake, BigQuery or cloud data services.
• Ability to connect architecture decisions to business outcomes and explain trade-offs.

Responsibilities

• 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.
• Design batch and real-time pipelines (ETL/ELT) across platforms.
• Help customers make informed architecture trade-offs on security, governance, performance, and cost.
• Ensure reliable operation with monitoring and recovery strategies.
• Lead technical discussions, demos, and proofs of concept for production deployment.

Skills

Data engineering

Data architecture

Cloud data services

Spark

Databricks

Snowflake

BigQuery

OCI multicloud

Customer-facing

Tools

Spark

Databricks

Snowflake

BigQuery

Job description

Bord is seeking a Senior Data and AI - Cloud Solution specialist to partner with customers and internal teams to design, deploy and optimize Oracle Cloud architectures for data platforms and AI use cases. You will drive adoption through discovery, design and production implementation in cloud environments.

The role emphasizes hands-on data engineering, architecture decisions, and collaboration with sales, engineering and product teams to deliver scalable data pipelines and analytics solutions.