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Today

Quality Data Engineer

Information Technology Senior Management Forum Spring, TX

Spring, TX

Today

$105k - $162k/yr Full time Big Data Cloud Data Engineering Data

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Job Description

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.

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