Quality Data Engineer

HP Inc.

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Spring, TX
Salary
$105,050–$161,800 / yr
Posted
4 days ago
Freshness
Confirmed live today
Closes
Mar 29, 2027

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $164k
This role $133k
$93k most similar roles pay here $214k

This role pays less than 69% of similar roles. Most pay $126,800–$202,075 — the shaded band above. At the midpoint, this role pays about $133k versus about $164k 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 116 open roles on FindRole.

Listed pay typically runs $130,700–$205,200 across 97 roles with salary data.

Most-posted roles

View all roles at HP Inc.

At a glance

TL;DR · Quality Data Engineer

The Quality Data Engineer leads a data engineering team to support application projects and collaborate with cross-functional teams on integrating deliverables. This role involves designing enterprise-wide data architectures, including warehouses and lakes, while managing complex databases and resolving critical incidents. The individual will develop data models, oversee model conversions, and build robust pipelines for AI/ML enablement and industrialization. Key responsibilities include establishing governance frameworks, ensuring security compliance, and driving the adoption of modern technologies like GenAI and streaming architectures. Technical requirements include proficiency in Python, SQL, and Scala or Java, alongside experience with AWS, Azure, Apache Spark, and NoSQL systems. The role addresses complex data engineering challenges by creating scalable infrastructure for advanced analytics, automated reporting, and high-performance data platforms to support large-scale structured and unstructured data environments.

What you'll do

  • Design and manage enterprise-wide data architectures including warehouses, lakes, and mesh frameworks.
  • Develop and maintain complex data pipelines for batch, streaming, and real-time processing.
  • Build and optimize feature engineering frameworks and MLOps workflows to productionize AI/ML models.
  • Establish data modeling standards, governance rules, and automated interoperability protocols.
  • Ensure all data systems comply with security, privacy, and quality monitoring standards.
  • Translate business goals into technical capabilities for analytics, reporting, and self-service tools.
  • Lead the adoption of modern technologies like GenAI, cloud-native platforms, and distributed systems.

What we're looking for

  • A four-year or graduate degree in Computer Science, Information Systems, Engineering, Statistics, Mathematics, Machine Learning, or Data Analytics.
  • 7 to 10 years of work experience in analytics, data science, reporting, or a related field (preferred).
  • Proficiency in Python and SQL is mandatory.
  • Experience with cloud platforms including AWS and Azure for data services, analytics, and storage.
  • Expertise in data warehousing, data lakes, ETL/ELT processes, and pipeline orchestration.
  • Experience with streaming systems, MLOps pipelines, and modern architectures like Data Mesh or Medallion.
  • Knowledge of Apache Spark, NoSQL, and Java (preferred).
  • Relevant Data Analytics certifications (preferred).

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