Jobs and Careers

Director of Enterprise Data Privacy Engineering

United Statesfull_timeVerifiedPosted 5 Feb 2026

💰 $250,000/yr($174,000/yr – $250,000/yr)

About the role

Description -

Role Purpose: This role will elevate data privacy from a compliance obligation to an AI-driven strategic business enabler. The Director will design and execute HP’s global data privacy and protection strategy by building an AI-first privacy architecture that embeds reusable frameworks and automation into enterprise data platforms. By combining technical depth with business acumen, this leader will ensure privacy accelerates innovation, drives operational efficiency, strengthens customer trust, and unlocks new market opportunities, aligning to business roadmap.

Why This Role Matters

Architect for Scale & Speed: Build privacy architecture that is modular, reusable, and automated, enabling rapid deployment of data products.
AI-First Culture: Infuse AI into every privacy process - classification, compliance, monitoring - to create a self-learning, adaptive privacy ecosystem.
Business Impact: Position privacy as a competitive advantage, reducing compliance overhead while accelerating product delivery.

Key Responsibilities (Aligned with HP Leadership Principles)

Think Customer First

Make privacy a customer value proposition, ensuring trust and transparency in all data products.
Embed privacy-by-design into enterprise platforms and customer-facing applications.

Innovate for Growth

Design AI-first privacy architecture that automates compliance, risk prediction, and secure data engineering.
Develop privacy accelerators - frameworks, APIs, and SDKs - that integrate seamlessly into product development workflows.

Act with Integrity

Align all initiatives with HP Cybersecurity, Privacy, and Legal frameworks while maintaining business agility.
Ensure ethical AI practices and transparent governance dashboards.

Build for the Future

Define a long-term roadmap for AI-driven privacy automation, reducing manual effort and enabling continuous compliance.
Implement zero-trust principles, encryption, and cyber controls across HP’s data ecosystem without compromising innovation speed.

Work as One HP

Collaborate with Data Engineering, Product, Legal, and Cybersecurity teams to embed privacy into enterprise data platforms
Foster a culture where privacy is seen as an innovation enabler, not a blocker.

Strategic & Technical Focus Areas

AI-Driven Privacy Architecture: Automated classification, anomaly detection, compliance monitoring, and risk prediction.
Reusable Privacy Frameworks: Build modular components for encryption, tokenization, anonymization, and DLP integration.
Process Automation: Streamline privacy workflows across data lifecycle—design, build, deploy, monitor.
Enterprise Platforms: Operations Datawarehouse, Federated Data Lakehouse, Metadata Lakehouse—ensure privacy controls are embedded without performance trade-offs.

Qualifications & Requirements

Education & Experience

Bachelor’s or master’s degree in computer science, Engineering, or related field.
10+ years of progressive experience in data privacy, cybersecurity, or data protection, with enterprise-scale architecture expertise.
Proven leadership in AI-driven privacy engineering, automation, and data engineering solutions for customer consent and privacy compliance.

Technical Expertise

Hands-on experience with AI security tools, DLP solutions, and privacy-by-design principles.
Strong programming skills (e.g., Python, Java) and proficiency with data processing frameworks (e.g., Apache Spark, Hadoop).
Expertise in cloud platforms (AWS, Azure, GCP) and data storage technologies (SQL, NoSQL, Big Data).
Working knowledge of sensitive data management technologies (e.g., BigID) and data loss prevention techniques.
Deep understanding of global privacy regulations (GDPR, CCPA) and cyber frameworks (NIST, ISO 27001), with a proven track record of implementing robust compliance solutions.