Onsite AI/ML Engineer I — Edge-to-Cloud Data

Hewlett Packard Enterprise; San Jose (CA); On-site; USD 93,000 - 188,000; Full time

Job summary

Hewlett Packard Enterprise is seeking an entry‑level data engineer to develop and optimize data pipelines, ingest both structured and unstructured data, and build analytical models using Python, SQL, and ML libraries.

You will work with Databricks and IT data platforms, ensuring data quality and useful analytics, while collaborating with cross‑functional teams and stakeholders across the organization.

Qualifications

• Bachelor’s degree in computer science, engineering, data science, machine learning, or closely related quantitative discipline. Master’s degree is desirable.

Responsibilities

• Partner with cross‑functional teams to identify opportunities for data‑driven improvements and translate business needs into technical solutions.
• Ingest and integrate data from structured and unstructured enterprise systems, including Databricks and IT data platforms.
• Design and build curated data models and analytical layers to support reporting and downstream analytics.
• Develop, optimize, and maintain pipelines using SQL, Python, and orchestration tools.
• Clean, transform, and prepare datasets for reliable consumption across the business.
• Ensure data quality and observability across pipelines, workflows, and storage layers.
• Integrate new data sources, APIs, and event streams into the platform.
• Create clear data documentation and communicate technical concepts to non‑technical stakeholders.
• Stay current with modern data engineering tools, cloud technologies, and best practices.

Skills

Python

R

Java

Statistics

Linear algebra

Calculus

Optimization

Education

Bachelor's degree in computer science, engineering, data science, ML/AI

Master’s degree desirable

Tools

TensorFlow

PyTorch

scikit-learn

SQL

Tableau

Matplotlib

Job description

Hewlett Packard Enterprise is seeking an entry‑level data engineer to develop and optimize data pipelines, ingest both structured and unstructured data, and build analytical models using Python, SQL, and ML libraries.

You will work with Databricks and IT data platforms, ensuring data quality and useful analytics, while collaborating with cross‑functional teams and stakeholders across the organization.