Principal Engineer, Storage Data Science and Analytics

As a Principal Engineer for Data Science & Analytics, you will serve as the premier technical authority bridging advanced machine learning, GenAI, and big data analytics with HPE's next-generation cloud and storage ecosystem (HPE GreenLake and hybrid cloud).

In this role, you will lead the architectural strategy to extract, analyze, and operationalize intelligence from vast telemetry data pipelines generated by enterprise file, block, and object storage systems. Your work will directly impact time-to-market, cost reduction, and predictive data management frameworks (including AIOps, predictive infrastructure failure, storage deduplication, and quality of service tuning).

Architectural Vision: Define the organization-wide data architecture strategy and analytical roadmaps for software systems running across HPE’s hybrid cloud platform .

Storage Optimization: Develop predictive, prescriptive, and generative AI models to map data paths, enhance memory/space management, and predict capacity or hardware failure across global enterprise clusters.

AIOps & Smart Telemetry: Validate highly complex, distributed telemetry data from customer storage networks to uncover structured insights that drive automated mitigation and system reliability.

Scale & Deploy: Design, deploy, and scale machine learning and deep learning code to run reliably in worldwide production edge-to-cloud environments.

Pipeline Design: Collaborate with data engineering to establish standardized ELT patterns, big data storage views, and high-throughput, low-latency streaming pipelines (supporting Kafka, Spark, etc.).

Generative AI & Agentic Workflows: Integrate advanced LLM workflows, Retrieval-Augmented Generation (RAG), and agentic systems into storage customer support analytics and digital products to automate troubleshooting.

Cross-Functional Orchestration: Partner with product management, storage hardware engineers, and business executives to translate abstract business challenges into production-ready analytical solutions.

Mentorship & Culture: Provide career guidance, conduct design reviews, and actively mentor senior engineers and data scientists across multiple Scrum teams to foster an innovative technical community.

Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a highly technical, data-oriented discipline.

Experience: 10+ years of proven industry experience in software product development or enterprise data science, with a heavy emphasis on distributed systems, storage, or cloud infrastructure architectures.

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

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HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity .

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