This role pays less than
61%
of similar roles. Most pay
$173,200–$236,362
— the shaded band above.
At the midpoint, this role pays about
$191k
versus about
$205k
for comparable roles.
Based on 240 similar postings.
Employer
About HP Inc.
HP Inc. is a global technology company that develops and sells personal computers, printers, and related supplies and services. Its products include laptops, desktops, workstations, and printing solutions for consumers and businesses worldwide.
HP Inc. currently has
104 open roles
on FindRole.
Listed pay typically runs
$130,700–$205,200
across 90 roles with salary data.
The Principal Data Privacy Architect leads and oversees complex, cross-functional privacy and data protection programs from strategy through implementation. This role involves designing and implementing scalable, AI-ready data privacy architecture across enterprise environments, including data warehouses, lakehouses, and vector databases. The architect builds reusable privacy engineering components such as APIs, SDKs, and policy-as-code controls while ensuring compliance with global regulations like GDPR, CCPA/CPRA, and LGPD. Key responsibilities include developing guardrails for generative AI, RAG pipelines, and automated data workflows, alongside implementing technical measures like encryption, tokenization, and anonymization. The role requires expertise in Python, Java, SQL, Spark, and infrastructure-as-code. The architect collaborates with engineering, legal, and cybersecurity teams to solve complex problems regarding data sovereignty, consent enforcement, and sensitive data protection within large, global data ecosystems to ensure secure, compliant data processing.
Python
SQL
AWS
Azure
Apache Spark
Apache Kafka
Data Warehousing
Data Lake
Lakehouse
MLOps
ETL
ELT
Scala
Java
Data Mesh
Medallion Architecture
Big Data
Agile Methodology
GenAI
Python
Go
Java
Scala
C++
Rust
Microservices
APIs
Data Governance
Encryption
Anonymization
Pseudonymization
Machine Learning
Data Pipelines
Audit Logging
Threat Modeling
Data Lineage
Privacy-by-Design
Differential Privacy
Federated Learning
On-device Processing
Tokenization
Data De-identification
AI
GDPR
CCPA
Privacy Engineering
Software Development
Infrastructure
Data Governance
Model Inference Privacy