Data Engineer

PSS Cross Country Infrastructure Solutions is hiring a Data Engineer in Houston, TX (onsite). In this role, you’ll design and operate the data architecture that supports business systems and analytics, including how data is structured for AI-powered applications. If you enjoy building reliable pipelines, setting clear standards, and collaborating across teams to keep data consistent and trustworthy, this position is built for that work.

What you’ll do

• Design canonical, well-documented data models for core business entities such as customers, projects, products, contracts, and finance, so multiple systems and teams can use a single source of truth.
• Evaluate and evolve schemas as business requirements and systems change, keeping an eye on long-term maintainability.
• Set and enforce data modeling standards, naming conventions, and documentation practices.
• Build and maintain ETL/ELT pipelines to move data from sources like ERP, CRM, operational databases, vendor feeds, and files into a cloud data warehouse.
• Monitor data quality and pipeline health, troubleshoot issues early at the source, and prevent downstream breakage.
• Integrate new data sources, including third-party platforms and vendor APIs, without duplicating effort or creating conflicting versions.
• Define and maintain data classification standards (for sensitive financial, contractual, or customer data) and ensure consistent application across systems.
• Support access control and audit needs by maintaining traceable data lineage and usage.
• Maintain a data dictionary and documentation so teams can find and trust the data they need.
• Design data structures and access patterns with consumption in mind, including AI/LLM-powered applications that depend on well-scoped, accurate context.
• Apply minimum-necessary-data principles when structuring data surfaced through AI features, partnering with application and security teams.
• Use working knowledge of retrieval-augmented generation and LLM context assembly to make informed schema and access decisions (not as a machine learning role).
• Translate reporting and application needs into sound data models with engineering, product, and business teams.
• Serve as a technical point of contact for data-related questions across multiple concurrent projects.

What you bring

• 4+ years of experience in data engineering or data architecture, including hands-on schema or data model design in production.
• Strong SQL skills and experience with a cloud data warehouse (preferred: Snowflake and MSFT SQL Server).
• Experience with ETL/ELT pipeline development and maintenance.
• Solid understanding of data governance: classification, access control, and documentation practices.
• Working knowledge of how modern AI/LLM applications consume data, including context windows and retrieval-augmented generation fundamentals, with an emphasis on minimizing and scoping data.
• Strong communication skills and comfort serving as the go-to person for data questions.

Tools you’ll use

SQL, Snowflake, MSFT SQL Server, ETL/ELT, Power BI, GitHub Actions, AWS, Python

Preferred and nice to have

• Preferred: Experience in a distribution, industrial supply, or ERP-adjacent environment; familiarity integrating third-party SaaS via API; experience with CI/CD tooling (for example, GitHub Actions) and cloud application environments (for example, AWS); experience consolidating multiple data models into a shared standard.
• Nice to have: Exposure to BI/reporting tools (for example, Power BI) and how they consume the underlying data model; working knowledge of Python.