Quality Data Engineer

Engg; Spring, Northern (TX, KY); Hybrid; USD 105,000 - 162,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Paid holidays

Parental leave

Job summary

HP is hiring a Quality Data Engineer in Spring, Texas to lead the data engineering team and drive enterprise data architectures for large-scale projects.

The role partners with cross-functional teams to deliver scalable data platforms, implement governance, and accelerate AI/ML initiatives while mentoring junior staff.

Qualifications

• Four-year or Graduate Degree in Computer Science, Information Systems, Engineering, Statistics/Mathematics, Machine Learning, Data Analytics.
• 7–10 years of experience in analytics, data engineering, or related field.

Responsibilities

• Lead data engineering for application projects and mentor engineers.
• Design enterprise data architectures (data lakes/warehouses) and govern data platforms.
• Develop scalable data pipelines and real-time data systems; ensure performance and security.
• Collaborate with cross-functional teams on AI/ML readiness and governance frameworks.

Skills

Python

SQL

Spark

Data Modeling

MLOps

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field

Tools

AWS

Azure

Data Lakes

Data Warehousing

ETL/ELT

Spark

Job description

# Quality Data EngineerHP · Spring, Texas, United States of AmericaLocation: Spring, Texas, United States of AmericaSalary: $105,050 to $161,800 USDExperience: 7+ yearsFunding: ~$18.5BPosted: Sep 30, 2026HP is hiring a Quality Data Engineer based in Spring, Texas, United States of America. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.Apply directly at HP## Role detailsQuality Data Engineer Description - This role is responsible for leading the data engineering team supporting application projects and collaborating with cross-functional teams to ensure integration of data engineering deliverables with project outcomes. The role contributes to solution development for complex deals and oversees the development and maintenance of intricate databases. The role takes charge of resolving critical database incidents, produces data models, and leads model conversion efforts. The role also provides expert guidance, exercises independent judgment, and fosters productive relationships while mentoring lower-level employees. Responsibilities: Data Architecture Strategy Design the enterprise-wide blueprint for how data is stored, integrated, accessed, and governed Manage the technical platforms that enable downstream insights, solutions, etc Design PS Quality data warehouses / data lakes Determine architectural patterns (e.g., medallion architecture, data mesh, data fabric) Establish data standards and automated interoperability rules Data Architecture & Platform Leadership Designing data warehouses / data lakes that meets Quality Business Requirements Define and implement enterprise-grade data architectures (batch, streaming, real-time) for large-scale structured and unstructured data. Design scalable, secure, and high-performance data platforms supporting BI, advanced analytics, and AI/ML use cases. Establish data modeling standards, and reusable frameworks across the organization. Data Strategy & Transformation Lead enterprise data strategy , aligning data initiatives with business, AI, and digital transformation goals. Identify and prioritize high-value analytics and AI opportunities leveraging telemetry, operational, and product data. Drive data monetization, standardization, and governance frameworks. Define roadmap for modern data stack adoption (cloud-native, lakehouse, streaming, GenAI-ready architectures). AI/ML Enablement & Industrialization Partner closely with Data Scientists to productionize ML/AI models into scalable systems. Build and optimize data pipelines, feature engineering frameworks, and MLOps workflows. Engineering Execution & Innovation Lead the design, development, and deployment of complex data pipelines and distributed systems. Drive adoption of new technologies (GenAI, agentic systems, streaming architectures, data mesh) . Ensure solutions meet performance, reliability, and cost optimization goals . Governance, Security & Compliance Ensure adherence to data governance, privacy, security, and compliance standards in alignment with HP Cybersecurity and privacy guidlines Maintain master data management, access controls, audits, metadata, management, and data hierarchy Establish data quality frameworks, lineage, observability, and monitoring mechanisms. Implement best practices across data lifecycle management. Cross-Functional Leadership & Influence Influence executive leadership, architecture boards, and cross-functional stakeholders on data strategy decisions. Act as a thought leader in data engineering and AI data ecosystems. Represent the organization in industry forums, publications, and innovation initiatives. Business Alignment Translate business goals into platform capabilities Faster automated analytics Enhanced AI/ML readiness Self-Service Tools Operational Reporting Enable data-driven decision making Education & Experience Recommended: Four-year or Graduate Degree in Computer Science, Information Systems, Engineering, Statistics/ Mathematics, Machine Learning, Data Analytics, and demonstrated competence. 7-10 years of work experience, preferably in analytics, data science, reporting, or a related field. Technical Expertise Strong experience in: Cloud platforms: AWS, Azure (data services, analytics, storage) Data platforms: Data Lakes, Lakehouse, Data Warehousing ETL/ELT and pipeline orchestration Programming: Python, SQL (mandatory) Scala/Java (good to have) Experience with: Streaming and real-time data systems Data modeling and governance MLOps / model deployment pipelines Modern architecture (Data Mesh, Medallion, API-driven data services) Preferred Certifications • Data Analytics Certifications Knowledge & Skills • Agile Methodology • Amazon Web Services • Apache Spark • Automation • Big Data • Computer Science • Data Analysis • Data Architecture • Data Engineering • Data Modeling • Data Warehousing • Extract Transform Load (ETL) • Java (Programming Language) • Machine Learning • Microsoft Azure • NoSQL • Python (Programming Language) • Scalability • Software Engineering • SQL (Programming Language) Cross-Org Skills • Effective Communication • Results Orientation • Learning Agility • Digital Fluency • Customer Centricity Impact & Scope • Impacts function and leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives. Complexity • Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors. Disclaimer • This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. The pay range for this role is $105,050 to $161,800 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional