Quality Data Engineer

HP is building and scaling data platforms that help application teams deliver insights, analytics, and AI-enabled capabilities. In this onsite role in Spring, TX, you will lead enterprise data engineering efforts, shaping how data is architected, governed, and productionized across batch, streaming, and real-time use cases.

You will work with cross-functional partners to modernize the data stack, establish standards for interoperability and modeling, and enable scalable pipelines that support BI, advanced analytics, and AI/ML systems.

Key Responsibilities

• Design an enterprise-wide blueprint for how data is stored, integrated, accessed, and governed.
• Manage the technical platforms that enable downstream insights and solutions.
• Design PS Quality data warehouses and data lakes, including data modeling standards and reusable frameworks.
• Define architectural patterns such as medallion architecture, data mesh, and data fabric.
• Establish data standards and automated interoperability rules.
• Build enterprise-grade data architectures for large-scale structured and unstructured data using batch, streaming, and real-time approaches.
• Develop scalable, secure, high-performance data platforms for BI, advanced analytics, and AI/ML use cases.
• Lead enterprise data strategy aligned with business, AI, and digital transformation goals.
• Identify and prioritize high-value analytics and AI opportunities using telemetry, operational, and product data.
• Drive data monetization, standardization, and governance frameworks.
• Define roadmaps 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 and workflows (including feature engineering and MLOps).
• Lead the design, development, and deployment of complex data pipelines and distributed systems.
• Influence executive leadership, architecture boards, and cross-functional stakeholders on data strategy decisions.
• 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 management, and data hierarchy.
• Establish data quality frameworks, lineage, observability, and monitoring mechanisms, and apply best practices across the data lifecycle.
• Represent HP in industry forums, publications, and innovation initiatives, and translate business goals into platform capabilities.
• Support complex problem solving that requires in-depth analysis of multiple factors; provide expertise to functional project teams and contribute to cross-functional initiatives.

Required Qualifications

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

Technology Stack

• 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

Benefits

• Health, dental, 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)

Preferred Certification

• Data Analytics Certifications

Other Details

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