Senior Data Platform Architect for AI & Analytics

HP; Georgia; On-site; USD 147,000 - 231,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Disability insurance

Employee assistance program

Flexible spending account

Life insurance

Generous time off policies

11 paid holidays

Job summary

HP seeks a Principal Data Architect to lead enterprise data platform architecture, data strategy, and AI/ML enablement. You will own data ecosystems end-to-end, partner with data science and AI teams, and drive governance, security, and scalable architectures across the organization.

The role emphasizes building scalable data warehouses/lakes, defining data standards, and guiding the modern data stack adoption to empower BI, analytics, and GenAI-ready solutions.

Qualifications

• Experience in designing enterprise data platforms and data strategy.
• Ability to translate business priorities into scalable, AI-ready data architecture.
• Strong knowledge of data governance, quality, and security best practices.
• Experience with cloud-native, lakehouse, streaming, and GenAI-ready architectures.

Responsibilities

• Lead enterprise data architecture strategy and platform leadership.
• Design scalable data warehouses and data lakes; define patterns (data mesh, medallion, etc.).
• Drive data monetization, governance, and modern data stack adoption.
• Partner with Data Science and AI teams to productionize ML/AI models.

Skills

Agile Methodology

Amazon Web Services

Apache Hadoop

Apache Kafka

Apache Spark

Big Data

Computer Science

Data Analysis

Data Engineering

Data Modeling

Data Pipelines

Data Warehousing

ETL

Java

Machine Learning

Microsoft Azure

Python

Scala

Scalability

SQL

Tools

Apache Hadoop

Apache Kafka

Apache Spark

Amazon Web Services

Microsoft Azure

Java

Python

Scala

SQL

ETL

Job description

HP seeks a Principal Data Architect to lead enterprise data platform architecture, data strategy, and AI/ML enablement. You will own data ecosystems end-to-end, partner with data science and AI teams, and drive governance, security, and scalable architectures across the organization.

The role emphasizes building scalable data warehouses/lakes, defining data standards, and guiding the modern data stack adoption to empower BI, analytics, and GenAI-ready solutions.