Quality Data Engineer

Spring, TX (onsite) full-time role with 25% travel and relocation available. Lead enterprise data engineering work with a focus on quality, governance, and scalable platforms that enable faster analytics and AI/ML outcomes. Salary range: USD 105,050 - 161,800 per year.

What you will bring

• 7+ years of relevant experience (7-10 years preferred)
• A four-year or graduate degree in Computer Science, Information Systems, Engineering, Statistics/Mathematics, Machine Learning, or Data Analytics
• Strong experience with AWS and/or Azure (data services, analytics, storage)
• Proven background building data lakes, lakehouse, and data warehousing solutions
• Hands-on development with ETL/ELT and pipeline orchestration
• Strong programming skills in Python and SQL (mandatory)
• Knowledge of streaming and real-time data systems
• Experience with data modeling and governance, plus MLOps and model deployment pipelines
• Familiarity with modern architectures such as Data Mesh, Medallion, and API-driven data services

How you will help the business

• Lead a data engineering team supporting application projects and coordinate with cross-functional partners to align data deliverables with project outcomes
• Drive the design and ongoing maintenance of enterprise-grade data architectures across batch, streaming, and real-time environments for both structured and unstructured data
• Design PS Quality data warehouses and data lakes that meet quality business requirements
• Establish data standards, automated interoperability rules, and reusable modeling frameworks
• Define and implement governance practices including privacy, security, and compliance aligned with HP Cybersecurity and privacy guidelines
• Maintain master data management, access controls, audits, metadata, and data hierarchy
• Create and operationalize data quality frameworks with lineage, observability, and monitoring mechanisms across the data lifecycle
• Prioritize high-value analytics and AI opportunities using telemetry, operational, and product data
• Partner with Data Scientists to productionize ML/AI models into scalable systems
• Build and optimize data pipelines, feature engineering frameworks, and MLOps workflows
• Drive adoption of new technologies such as GenAI, agentic systems, streaming architectures, and data mesh
• Ensure solutions meet goals for performance, reliability, and cost optimization
• Influence executive leadership and architecture stakeholders on data strategy decisions
• Represent the organization through industry forums, publications, and innovation initiatives

Additional responsibilities

• Contribute to solution development for complex deals
• Resolve critical database incidents and lead model conversion efforts
• Build the enterprise blueprint for how data is stored, integrated, accessed, and governed
• Manage technical platforms that enable downstream insights and solutions
• Translate business goals into platform capabilities, including faster automated analytics, enhanced AI/ML readiness, self-service tools, and operational reporting
• Drive data monetization, standardization, and governance frameworks
• Define the roadmap for modern data stack adoption (cloud-native, lakehouse, streaming, and GenAI-ready architectures)
• Mentor lower-level employees and exercise independent judgment to guide outcomes

Compensation and benefits

• Salary: USD 105,050 - 161,800 per year
• Health insurance, Dental insurance, Vision insurance
• Long term/short term disability
• Employee assistance program, Flexible spending account
• Life insurance
• Generous time off, including fully paid parental leave (4-12 weeks based on tenure) and 11 paid holidays, plus additional flexible paid vacation and sick leave (US benefits overview)

Technology and methods

• AWS, Azure, Apache Spark, NoSQL
• Data Lakes, Lakehouse, Data Warehousing
• ETL/ELT, pipeline orchestration
• Streaming and real-time data systems
• Data Mesh, Medallion, API-driven data services
• GenAI, agentic systems, MLOps and MLOps workflows
• Agile Methodology

Impact and scope

This position impacts functional project teams through leadership and expert guidance, including participation in cross-functional initiatives. Work involves complex problems where analysis requires in-depth evaluation of multiple factors.

Preferred certifications: Data Analytics certifications.

Job category: Data & Information Technology. Schedule: Full time. Shift premium: None.

Note: This description reflects the general nature and level of work. Duties, skills, and responsibilities may change as needed by management.