About The Position
Modern Data Architecture Expertise – 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. Multi-Platform and Lakehouse Technology Proficiency – 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. Generative AI & Agentic Applications – 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. AI/ML Solution Engineering in Lakehouse Contexts – 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. Pre-Sales Engineering Excellence – 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. Thought Leadership & Enablement – Experience producing high-quality technical assets (white papers, solution accelerators, blogs, videos) and delivering content at customer briefings, industry conferences, and internal enablement sessions. Continuous Learning & Influence – 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.
Requirements
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
