Data Engineer

In Houston, TX, PSS Cross Country Infrastructure Solutions is hiring a Data Engineer to design and maintain the data architecture that supports business systems and analytics. This role focuses on how data is modeled, transported, classified, and governed across the organization, including collaboration to keep data consistent, documented, and trustworthy. You will also maintain working knowledge of how AI-powered applications consume structured context, without needing to be a machine learning specialist. What you’ll do Design canonical, well-documented data models for core business entities such as customers, projects, products, contracts, and finance, enabling multiple systems and teams to use a single source of truth. Evaluate and evolve schemas as business needs and systems change, balancing new requirements with long-term maintainability . Set and enforce data modeling standards , including naming conventions and documentation practices. Build and maintain ETL/ELT pipelines to move data from sources including ERP, CRM, operational databases, vendor feeds, and files into a cloud data warehouse . Monitor data quality and pipeline health , troubleshoot issues, and resolve problems at the source rather than downstream. Integrate new data sources, including third-party platforms and vendor APIs , into the existing architecture without duplicating efforts or creating conflicting versions of the same data. Define and apply data classification standards for sensitive financial, contractual, and customer data across systems. Support access control and audit needs by maintaining traceable data lineage and usage information. Maintain a data dictionary and supporting documentation so other teams can locate and trust the data they need. Design data structures and access patterns with intended consumption in mind, including AI/LLM-powered applications that require well-scoped, accurate context. Apply minimum-necessary-data principles when structuring datasets exposed through AI features, working with application and security teams. Stay current on how retrieval-augmented generation (RAG) and LLM context assembly work to inform schema and access decisions. Partner with engineering, product, and business teams to translate reporting and application requirements into sound data models. Act as a technical point of contact for data-related questions across multiple concurrent projects. Required qualifications 4+ years of experience in data engineering or data architecture, including hands-on schema and data model design in a production environment. Strong SQL skills and experience with a cloud data warehouse; Snowflake and MSFT SQL Server are preferred. Experience with the SQL query language. Experience building and maintaining ETL/ELT pipelines . Solid understanding of data governance fundamentals, including classification , access control , and documentation . Working knowledge of how modern AI/LLM applications consume data, including context windows and retrieval-augmented generation basics, with an emphasis on why minimizing and scoping data matters. Strong communication skills and comfort serving as a go-to resource for data questions. Technologies 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. Preferred: Familiarity with integrating third-party SaaS platforms via API. Preferred: Experience with CI/CD tooling (for example, GitHub Actions) and cloud application environments (for example, AWS). Preferred: Experience consolidating multiple existing data models into a shared standard. Nice to have: Exposure to BI/reporting tools such as Power BI and how they consume the underlying data model. Nice to have: Working knowledge of Python. Location: Houston, TX (onsite). Minimum experience: 4 years. #J-18808-Ljbffr