Senior AI Cloud Engineer: GenAI, Data & Infra (Remote)

Bluelightconsulting

Quilmes

Remote

ARS 185,448,000 - 231,811,000

Full time

5 days ago
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Job summary

Pearster is hiring a Senior Data and AI - Cloud Solution to design, build, and deploy AI-enabled Oracle Cloud architectures that address real customer problems and accelerate cloud adoption.

You will partner with customers, sales, engineering, and product teams, lead technical discussions, proofs of concept, and enable production deployments while focusing on data platforms, AI use cases, and scalable, secure cloud solutions.

Qualifications

  • 8+ years of experience in data engineering or data architecture.
  • 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.
  • Ability to connect architecture decisions to business outcomes and explain trade-offs to different audiences.

Responsibilities

  • Discover customer data challenges 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 with ETL/ELT and cross-platform integration.
  • Lead technical discussions, demos, and proofs of concept.
  • Help customers bring validated solutions into production.

Skills

Data engineering
Data architecture
Distributed processing
Cloud data services
OCI/multicloud
Spark
Databricks
Snowflake
BigQuery

Education

Bachelor's degree in CS/Engineering

Tools

Spark
Databricks
Snowflake
BigQuery
OCI

Job description

Pearster is hiring a Senior Data and AI - Cloud Solution to design, build, and deploy AI-enabled Oracle Cloud architectures that address real customer problems and accelerate cloud adoption.

You will partner with customers, sales, engineering, and product teams, lead technical discussions, proofs of concept, and enable production deployments while focusing on data platforms, AI use cases, and scalable, secure cloud solutions.

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