Data Engineer

PSS Cross Country Infrastructure Solutions is hiring a Data Engineer for an onsite role in Houston, TX. In this position, you will design and maintain the data architecture that supports business systems and analytics, with working knowledge of how AI-powered applications consume data for scoped, accurate context.

You will take ownership of how data is modeled, moved, and governed across the organization, partnering with engineering, product, and business teams to keep data consistent, documented, and trustworthy.

Key Responsibilities

• Design canonical, well-documented data models for core business entities such as customers, projects, products, contracts, and finance as a shared source of truth.
• Evaluate and evolve schemas as requirements grow, maintaining a balance between new needs and long-term maintainability.
• Define and apply data modeling standards, naming conventions, and documentation practices.
• Build and maintain ETL/ELT pipelines to move data reliably from source systems (ERP, CRM, operational databases, vendor feeds, files) into a cloud data warehouse.
• Monitor data quality and pipeline health, troubleshooting issues at the source rather than downstream.
• Integrate new data sources, including third-party platforms and vendor APIs, into the architecture without duplicating effort or creating conflicting versions.
• Define and maintain data classification standards for sensitive financial, contractual, or customer data and ensure consistent application.
• Support access control and audit requirements by maintaining traceable data lineage and usage.
• Maintain a data dictionary and supporting documentation so other teams can find and trust required datasets.
• Design data structures and access patterns with an understanding of consumption needs, including AI/LLM-powered applications that rely on well-scoped context rather than raw database access.
• Apply minimum-necessary-data principles for data exposed through AI features, coordinating with application and security teams.
• Stay current on how retrieval-augmented generation and LLM context assembly work to inform schema and access decisions (working knowledge, not a machine learning role).
• Translate reporting and application needs into sound data models in collaboration with engineering, product, and business teams.
• Serve as a technical point of contact for data-related questions across multiple concurrent projects.

Requirements

• 4+ years of experience in data engineering or data architecture, including hands-on production schema and data model design.
• Strong SQL skills and experience with a cloud data warehouse (preferred: Snowflake and MSFT SQL Server).
• Experience using SQL query language.
• Experience building and maintaining ETL/ELT pipelines.
• Solid understanding of data governance fundamentals, including 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 emphasis on why scoping and minimizing data matters.
• Strong communication skills and comfort acting as the main contact for data questions across teams.

Technologies

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

Preferred

• Experience in a distribution, industrial supply, or ERP-adjacent environment.
• Familiarity with integrating third-party SaaS platforms via API.
• Experience with CI/CD tooling (e.g., GitHub Actions) and cloud application environments (e.g., AWS).
• Experience consolidating multiple existing data models into a shared standard.

Nice to Have

• Exposure to BI/reporting tools (e.g., Power BI) and how they consume the underlying data model.
• Working knowledge of Python.

Location: Houston, TX (onsite)
Minimum Experience: 4 years