Data Engineer

Sorry, this job was removed at 08:08 p.m. (UTC) on Thursday, Sep 24, 2026
Houston, TX, USA
In-Office
Mid level
Industrial
The Role
Designs and maintains data architecture, canonical schemas, ETL/ELT pipelines, cloud data warehouse integrations, governance standards, data lineage, and documentation. Partners with engineering, product, business teams, and vendors to ensure reliable, trustworthy data. Designs data access patterns for AI and LLM applications, including retrieval-augmented generation and minimum-necessary-data principles.
Summary Generated by Built In

Job Description:

This role is in based in Houston, TX. Candidates currently located in the Houston, TX are are encouraged to apply.


We're looking for a Data Engineer to design and maintain the data architecture that powers our business systems and analytics — and possess a working knowledge of AI-powered applications as they become part of that landscape. You'll own how data is modeled, moved, and governed across the organization, and make sure that foundation is solid enough for both traditional reporting and modern AI-driven tools to build on.

This role sits at the center of a lot of cross-functional work: you'll partner with application teams, business stakeholders, and vendors to make sure data is structured consistently, documented clearly, and trustworthy wherever it's used.


Responsibilities

Data architecture & schema design

· 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.

Pipelines & integration

· 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.

Data governance

· 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.

AI-aware data engineering

· 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.

Collaboration

· 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.


Technical Skills

Required

· 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.

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

Company Statement:

PSS Industrial provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristics protected by federal, state, or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Skills Required

  • 4+ years of experience in data engineering or data architecture, including production schema or data model design
  • Strong SQL skills
  • Experience with a cloud data warehouse; Snowflake and Microsoft SQL Server preferred
  • Experience building and maintaining ETL/ELT pipelines
  • Understanding of data governance, including classification, access control, and documentation
  • Working knowledge of AI/LLM data consumption, context windows, retrieval-augmented generation, and data minimization
  • Strong communication skills and ability to support cross-functional data questions
  • Experience in distribution, industrial supply, or ERP-adjacent environments
  • Experience integrating third-party SaaS platforms through APIs
  • Experience with CI/CD tooling such as GitHub Actions and cloud environments such as AWS
  • Experience consolidating multiple data models into a shared standard
  • Exposure to BI or reporting tools such as Power BI
  • Working knowledge of Python

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The Company
355 Employees
Year Founded: 2014

What We Do

PSS Industrial Group (PSSI) is a Houston-headquartered value-added distributor serving contractors and industrial customers across the United States. It supplies pipeline consumables, MRO products, hand and power tools, safety products, material-handling solutions, pipe, valves and fittings, and related equipment and services. Through its regional supply-chain network, PSSI supports energy, infrastructure construction, maintenance, and other industrial markets, providing product expertise and distribution capabilities nationwide.

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