Quality Data Engineer

Build enterprise-grade data platforms at HP and help turn complex data into faster automated analytics, enhanced AI/ML readiness, and self-service tools. In Spring, TX (onsite), you will lead architecture and delivery across data warehousing, governance, streaming, and modern data stack roadmaps, while partnering with data science teams to productionize AI/ML.

What you’ll do

• Design the enterprise-wide blueprint for how data is stored, integrated, accessed, and governed
• Manage technical platforms that enable downstream insights and solutions
• Design HP PS Quality data warehouses and data lakes
• Define architectural patterns such as medallion architecture, data mesh, and data fabric
• Establish data standards and automated interoperability rules
• Implement enterprise-grade data architectures for batch, streaming, and real-time structured and unstructured data
• Build scalable, secure, high-performance data platforms for BI, advanced analytics, and AI/ML use cases
• Set data modeling standards and reusable frameworks across the organization
• Lead enterprise data strategy aligned 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 a roadmap for modern data stack adoption including cloud-native, lakehouse, streaming, and GenAI-ready architectures
• Partner with Data Scientists to productionize ML/AI models into scalable systems
• Create and optimize data pipelines, feature engineering frameworks, and MLOps workflows
• Lead the design, development, and deployment of complex data pipelines and distributed systems
• Drive adoption of new technologies including GenAI, agentic systems, streaming architectures, and data mesh
• Ensure performance, reliability, and cost optimization goals are met
• Ensure adherence to data governance, privacy, security, and compliance standards in alignment with HP Cybersecurity and privacy guidelines
• Maintain master data management, access controls, audits, metadata, and data hierarchy
• Establish data quality frameworks, lineage, observability, and monitoring mechanisms; apply best practices across the data lifecycle
• Influence executive leadership, architecture boards, and cross-functional stakeholders on data strategy decisions
• Represent HP in industry forums, publications, and innovation initiatives
• Work on complex problems requiring in-depth evaluation of multiple factors

Required qualifications

• Four-year or Graduate Degree in Computer Science, Information Systems, Engineering, Statistics/Mathematics, Machine Learning, Data Analytics, or demonstrated competence
• 7-10 years of work experience, preferably in analytics, data science, reporting, or a related field
• Strong experience with AWS and Azure (data services, analytics, storage)
• Strong experience with data platforms including Data Lakes, Lakehouse, and Data Warehousing
• Strong experience with ETL/ELT and pipeline orchestration
• Python and SQL (mandatory)
• Experience with streaming and real-time data systems
• Experience with data modeling and governance
• Experience with MLOps and model deployment pipelines
• Experience with modern architecture: Data Mesh, Medallion, and API-driven data services

Preferred certifications

• Data Analytics Certifications

Tools and technologies you may use

• AWS, Azure, Python, SQL, Scala, Java
• Apache Spark, NoSQL
• ETL, ELT, Data Lakes, Lakehouse, Data Warehousing
• Medallion architecture, data mesh, data fabric
• MLOps, GenAI, agentic systems, streaming architectures

Compensation, schedule, and logistics

• Salary: USD 105,050 - 161,800 per year
• Location: Spring, TX (onsite)
• Schedule: Full time
• Shift premium: No shift premium (United States of America)
• Travel: 25%
• Relocation: Yes
• Job category: Data & Information Technology

HP benefits

• Health insurance, dental insurance, and vision insurance
• Long term/short term disability insurance
• Employee assistance program
• Flexible spending account
• Life insurance
• 4-12 weeks fully paid parental leave based on tenure
• 11 paid holidays
• Additional flexible paid vacation and sick leave (US benefits overview)

Skills that support success

• Agile methodology
• Automation, big data, data analysis, and data engineering
• Digital fluency and customer centricity
• Effective communication, results orientation, learning agility