Within the Forward Deployment Engineering (FDE) Unit, the Advisory AI Data Specialist is the data expert who makes customer data ready for AI and GenAI workloads. You focus on removing data bottlenecks so FDE Units can move quickly from concept to live, value-generating AI workloads on Dell infrastructure. You will work with customer teams to map data landscapes, build integrations and pipelines, and configure governance and access controls so that data used in proofs of value is secure, compliant, and scalable to production.

Join us to do the best work of your career and make a profound social impact as an Advisory AI Data Specialist on our Forward Deployment Engineering (FDE) Team in Sydney.

What You’ll Achieve

•  Lead data readiness assessments to understand what data is available, how it is used, and how it can support AI use cases
• Build and improve data pipelines and integrations that deliver AI-ready data for AI and GenAI workloads
• Design and configure governance and compliance controls that enable secure and compliant use of data for AI
• Help ensure that PoV data flows are designed with production scale, performance, and operations in mind
• Partner with AI Architects, AI Strategists, and customer stakeholders to align data work with overall AI priorities and operating models

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• Lead data readiness assessments for FDE engagements, including cataloging data assets, ownership, quality, accessibility, and AI suitability
• Perform hands-on data integration and transformation work to prepare AI-ready datasets for PoV and production solutions
• Design and configure data governance and compliance controls (e.g., access control, sensitive data handling, retention, auditability) in line with regulatory and organizational needs
• Define integration patterns and pipelines that deliver AI-ready data with appropriate security, risk, and privacy controls
• Ensure PoV pipelines are production-aware from the start, including patterns for monitoring, reliability, performance, and maintainability
• Collaborate closely with AI Architects to align data flows with the AI software stack and avoid data-related blockers
• Work with AI Strategists and customer stakeholders to align data work with AI governance frameworks, operating models, and stewardship processes
• Contribute to documentation such as data flow diagrams, data catalogs, governance artifacts, and runbooks for AI data operations
• Coach customer data engineers and platform teams on building and maintaining AI-ready data pipelines and governance practices

Take the first step towards your dream career
Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:

Essential Requirements

• Typically, 5 or more years in data engineering, analytics platforms, or AI data roles within large or complex organizations.
• Experience running data readiness assessments and preparing data for analytics or AI use cases.
• Hands-on skills in building data integrations and ETL/ELT processes and transforming raw data into AI-ready formats.
• Experience configuring data governance and compliance controls for secure and compliant use of data, including sensitive data.
• Proven ability to scale data pipelines from pilot to production while maintaining performance, reliability, and compliance.
• Clear written and verbal communication skills to explain data flows, governance decisions, and operational requirements to technical and non-technical audiences.
• Ability to travel to customer sites and Dell locations as needed, in line with business requirements and applicable laws and Dell policies.

Desirable Requirements

• Bachelor’s degree in Computer Science, Data/Information Management, Engineering, or a related field.
• Experience delivering production data pipelines and integrations for analytics or AI/ML use cases.
• Familiarity with modern data platforms, ETL/ELT tooling, and AI/ML-related data patterns (e.g., feature stores, vectorization, RAG-related data flows).
• Experience collaborating with security, compliance, architecture, and business stakeholders on data and AI initiatives.