Quality Data Engineer

HP•Spring, TX

1d•$105,050 - $161,800•Remote

About The Position

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.

Requirements

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.
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)
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)
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)
Machine Learning
Microsoft Azure
NoSQL
Python (Programming Language)
Scalability
Software Engineering
SQL (Programming Language)
Effective Communication
Results Orientation
Learning Agility
Digital Fluency
Customer Centricity

Nice To Haves

Scala/Java (good to have)
Java (Programming Language)
Preferred Certifications: Data Analytics Certifications

Responsibilities

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
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.
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).
Partner closely with Data Scientists to productionize ML/AI models into scalable systems.
Build 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 (GenAI, agentic systems, streaming architectures, data mesh).
Ensure solutions meet performance, reliability, and cost optimization goals.
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.
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.
Translate business goals into platform capabilities
Faster automated analytics
Enhanced AI/ML readiness
Self-Service Tools
Operational Reporting
Enable data-driven decision making

Benefits

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 flexible paid vacation and sick leave (US benefits overview)