Data Engineer

Pipeline Supply Service LLC is seeking a Data Engineer to design and maintain the data architecture supporting business systems, analytics, and AI-powered applications. The role is responsible for data modeling, ETL/ELT pipelines, integrations, governance, data quality, and cross-functional collaboration.

Responsibilities

• Design canonical, well-documented data models for core business entities (customers, projects, products, contracts, finance, etc.) that multiple systems and teams can rely on as a single source of truth
• Evaluate and evolve schemas as the business and its systems grow — balancing new requirements against long-term maintainability
• Establish and enforce data modeling standards, naming conventions, and documentation practices
• Build and maintain ETL/ELT pipelines that move data reliably from source systems (ERP, CRM, operational databases, vendor feeds, files) into a cloud data warehouse
• Monitor data quality and pipeline health; troubleshoot and resolve data issues at the source rather than downstream
• Integrate new data sources — including third-party platforms and vendor APIs — into the existing architecture without duplicating effort or creating conflicting versions of the same data
• Define and maintain data classification standards (e.g., what counts as sensitive financial, contractual, or customer data) and ensure those standards are applied consistently across systems
• Support access control and audit requirements by ensuring data lineage and usage are traceable
• Maintain a data dictionary and related documentation so other teams can find and trust the data they need
• Design data structures and access patterns with an understanding of how they'll be consumed — including by AI/LLM-powered applications that rely on well-scoped, accurate context rather than raw database access
• Apply minimum-necessary-data principles when structuring data that will be surfaced through AI features, in partnership with application and security teams
• Stay current enough on how retrieval-augmented generation and LLM context assembly work to make informed schema and access decisions — this is a working-knowledge requirement, not a machine learning role
• Work with engineering, product, and business teams to translate reporting and application needs into sound data models
• Act as a technical resource and point of contact for data-related questions across multiple concurrent projects

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
• Exposure to BI/reporting tools (e.g., Power BI) and how they consume the underlying data model
• Working knowledge of Python
• Distribution industry experience
• Industrial supply experience
• ERP environment experience
• SaaS platform integration
• API integration
• CI/CD tooling
• GitHub Actions
• Cloud application environments
• AWS
• Data model consolidation
• Data standardization
• BI
• reporting tools
• Power BI
• Data model consumption
• Python

Benefits

• Hybrid work arrangement

Company

• Infrastructure product distribution and equipment rental for contractors
• Houston, Texas, USA
• https://pssigroup.com/
• Founded in 2011
• 201-500 employees

Qualifications

• 4+ years of experience in data engineering or data architecture, including hands-on schema/data model design in a production environment
• Strong SQL skills and experience with a cloud data warehouse (Snowflake and MSFT SQL Server preferred)
• Experience SQL query language
• Experience building and maintaining ETL/ELT pipelines
• Solid understanding of data governance fundamentals: classification, access control, and documentation practices
• Working knowledge of how modern AI/LLM applications consume data — context windows, retrieval-augmented generation, and the basics of why minimizing and scoping data matters for these systems
• Strong communication skills; comfortable being the person other teams come to for data questions
• 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
• Exposure to BI/reporting tools (e.g., Power BI) and how they consume the underlying data model
• Working knowledge of Python
• 4+ years of experience in data engineering or data architecture, including hands-on schema/data model design in a production environment.

Required skills

• Data Engineering, Data Architecture, Data Modeling, SQL, Cloud Data Warehousing, ETL/ELT Pipelines, Data Governance, Data Classification, Access Control, Data Lineage, Retrieval-Augmented Generation, LLM Context Assembly

Preferred skills

• Working knowledge of Python

Experience

• 4+ years