Vice President - Principal Data Engineer

Responsibilities

• Architect, build, deploy, and operate scalable ETL/ELT data pipelines supporting analytics, ML, and GenAI workloads.
• Use AI/ML and GenAI to design and build data pipelines, including: AI‑assisted pipeline and schema design; AI‑generated and optimized transformation logic and code; automated test generation, data validation, and performance tuning; AI‑driven documentation and operational runbooks.
• Apply AI/ML techniques to automate data engineering workflows, including ingestion, schema evolution, data quality checks, anomaly detection, and pipeline optimization.
• Build and maintain feature engineering pipelines, training datasets, and feedback loops for production ML and GenAI systems.
• Enable GenAI use cases, including unstructured data ingestion, retrieval pipelines (RAG), and governance‑aware AI data flows.
• Ensure enterprise standards for reliability, observability, lineage, security, and compliance across all data and AI pipelines.
• Partner with product, program, analytics, and AI teams in Agile delivery models to translate business needs into scalable AI‑enabled data solutions.
• Provide senior technical leadership through architecture reviews, mentoring, and setting data & AI engineering standards.
• Required Qualifications
• 12+ years of experience owning and operating large‑scale data engineering platforms in production.
• Strong hands‑on expertise in Python and SQL, with deep experience on cloud data platforms (AWS, Azure, or GCP).
• Proven experience architecting distributed, high‑performance data systems.
• Demonstrated experience using AI/ML or GenAI to design, build, or optimize data pipelines (not just consuming AI outputs).
• Strong experience supporting ML/AI systems in production, including feature pipelines, data validation, monitoring, and retraining support.
• Solid understanding of data modeling, performance tuning, DevOps/CI‑CD, and Agile delivery.
• Excellent communication skills and ability to operate in fast‑paced, cross‑functional environments.
• Preferred / Plus Skills
• Experience with GenAI/LLM ecosystems (e.g., RAG, vector data, prompt or model lifecycle support).
• Experience with microservices, APIs, and large‑scale analytics platforms.
• Prior experience leading or mentoring senior engineers (player‑coach model).
• Experience working in financial services or regulated environments.
• Why This Role
• This role goes beyond traditional data engineering. You will use AI to fundamentally change how data pipelines are designed, built, and operated, while delivering mission‑critical data and AI platforms at enterprise scale.

Benefits

Additional Information

About this role Role Overview Data and AI are central to our platform and competitive advantage. We are seeking a Senior / Principal Data Engineer (12+ years) to design, build, and operate large‑scale, enterprise data platforms, with deep AI/ML and GenAI expertise-not only enabling AI use cases, but using AI as a first‑class tool to design, build, and optimize data pipelines. This role is a hands‑on senior engineering position with architectural ownership, operating at the intersection of data engineering, AI/ML systems, and platform modernization.

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Company Intel

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