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Oracle · 2 months ago

Master Principal Cloud Architect, AI Data Platform

United States

Full-time

Remote

Lead/Staff

10+ years exp

Oracle is seeking a Master Principal Cloud Architect specializing in AI Data Platforms. The role involves designing modern data architectures, engaging with enterprise customers, and leading AI/ML solution engineering in lakehouse contexts.

Data GovernanceData ManagementEnterprise SoftwareInformation TechnologySaaSSoftware

No H1B

Responsibilities

Proven ability to design and position modern data lakehouse solutions, with hands-on experience in Delta Lake, Apache Iceberg, Spark, and medallion architecture patterns

Expert in architecting unified data platforms that blend the scalability of data lakes and manageability of warehouses

Deep familiarity with industry-leading data platforms such as Databricks, Snowflake, GCP BigQuery, AWS Redshift, and Microsoft Fabric

Skilled at articulating technical, architectural, and pricing differentiators, and navigating integration/migration scenarios in hybrid or multi-cloud settings

Proficient in Python for building PySpark data processing pipelines, general data science work using Jupyter notebooks, building AI Agents using Agentic frameworks such as LangChain and LangGraph

Hands-on experience with building and deploying AI assistants, agentic frameworks, vector databases, semantic enrichment processes, and the orchestration of enterprise AI workflows

Ability to translate complex enterprise AI requirements into actionable Oracle cloud-based solutions

Advanced capability in designing and operationalizing scalable data pipelines, MLOps workflows, and AI/ML model deployment using tools like Databricks ML, BigQuery ML, Snowpark, and open-source frameworks (Python, Spark MLlib) within data lakehouse architectures

Strong track record of engaging with enterprise customers, qualifying opportunities, shaping POCs, and driving adoption from pilot through to production and scale

Skilled at conducting effective discovery, technical presentations, and competitive positioning

Experience producing high-quality technical assets (white papers, solution accelerators, blogs, videos) and delivering content at customer briefings, industry conferences, and internal enablement sessions

Maintains expertise by staying at the forefront of evolving technologies and best practices in AI, data platform modernization, and cloud-native architectures

Able to influence product engineering and roadmap based on field insights and customer requirements

Qualification

Modern Data ArchitectureLakehouse TechnologyGenerative AI ApplicationsAI/ML Solution EngineeringPre-Sales EngineeringTechnical PresentationsThought LeadershipEnglish LanguageContinuous Learning

Required

10+ years of experience in relevant field

Proven ability to design and position modern data lakehouse solutions

Hands-on experience in Delta Lake, Apache Iceberg, Spark, and medallion architecture patterns

Expert in architecting unified data platforms that blend the scalability of data lakes and manageability of warehouses

Deep familiarity with industry-leading data platforms such as Databricks, Snowflake, GCP BigQuery, AWS Redshift, and Microsoft Fabric

Skilled at articulating technical, architectural, and pricing differentiators

Navigating integration/migration scenarios in hybrid or multi-cloud settings

Proficient in Python for building PySpark data processing pipelines

General data science work using Jupyter notebooks

Building AI Agents using Agentic frameworks such as LangChain and LangGraph

Hands-on experience with building and deploying AI assistants

Experience with agentic frameworks, vector databases, and semantic enrichment processes

Ability to translate complex enterprise AI requirements into actionable Oracle cloud-based solutions

Advanced capability in designing and operationalizing scalable data pipelines

Experience with MLOps workflows and AI/ML model deployment using tools like Databricks ML, BigQuery ML, Snowpark, and open-source frameworks (Python, Spark MLlib)

Strong track record of engaging with enterprise customers

Qualifying opportunities, shaping POCs, and driving adoption from pilot through to production and scale

Skilled at conducting effective discovery, technical presentations, and competitive positioning

Experience producing high-quality technical assets (white papers, solution accelerators, blogs, videos)

Delivering content at customer briefings, industry conferences, and internal enablement sessions

Maintains expertise by staying at the forefront of evolving technologies and best practices in AI, data platform modernization, and cloud-native architectures

Able to influence product engineering and roadmap based on field insights and customer requirements