Principal Engineer, Storage Data Science and Analytics

Overview

Principal Engineer for Storage Data Science and Analytics, serving as a technical authority bridging machine learning, GenAI, and big data analytics with HPE’s hybrid cloud and storage ecosystem.

What you'll do

• Lead architectural strategy to extract, analyze, and operationalize intelligence from telemetry data pipelines from enterprise file, block, and object storage systems.
• Define organization-wide data architecture strategy and analytical roadmaps for hybrid cloud software systems.
• Design, deploy, and scale machine learning and deep learning code for reliable production edge-to-cloud environments.
• Collaborate with data engineering to establish standardized ELT patterns and high-throughput, low-latency streaming pipelines.
• Integrate LLM workflows, RAG, and agentic systems into storage customer support analytics and digital products to automate troubleshooting.
• Partner with product management, storage hardware engineers, and business executives to translate business challenges into production-ready analytical solutions.
• Provide career guidance, conduct design reviews, and mentor senior engineers and data scientists across multiple Scrum teams.

What you'll need

• 10+ years of experience in software product development or enterprise data science, emphasizing distributed systems, storage, or cloud infrastructure architectures.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a highly technical, data-oriented discipline.
• Advanced mastery of machine learning algorithms including time-series forecasting, clustering, anomaly detection, and random forests.
• Concrete experience building and fine-tuning LLMs, prompt engineering, and leveraging vector databases.
• Expert programming in Python/Go-lang.
• Strong working knowledge of data structures, algorithmic complexity, and multi-threaded/multi-process programming.
• Experience building scalable data pipeline design and deployment in a multi-node environment.

Details

• Work mode: Onsite (primarily from an HPE office).
• Location: Bengaluru, Karnātaka, India.