IT Data Platform Engineer
Listed on 2026-02-28
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IT/Tech
Data Engineer, Data Analyst, Cloud Computing, Data Security
Company Overview
NRS is a leading provider of transportation & supply chain solutions. As a family‑owned and operated company, NRS has delivered smart logistics solutions to numerous Fortune 500 companies spanning over 70 years. Whether it’s NRT, Keystone, Keystone Fresh, or Keystone Capacity, our innovative energy drives us towards new and valuable solutions for our clients, even as we continuously grow and strengthen our network.
We are dedicated to creating a culture that empowers the individual and offers our associates the opportunity to apply their unique skill to the challenges facing our clients. In the office, the warehouse, or on the road, it is this commitment to our innovative spirit that unites us in a common mission to push boundaries in the logistics industry.
As a member of the Data & Analytics team within the Information Technology organization, reporting to the Manager of Data & Analytics, the Data Platform Engineer is directly responsible for building, operating, and automating internal platforms that abstract infrastructure, tooling, and operational complexity into reliable, self‑service capabilities for data engineers, analysts, and data scientists. This individual will play a critical role in scaling enterprise data platforms and tools, standardizing CI/CD processes, ML Ops and deployment frameworks, monitoring and optimizing systems to ensure performance and reduce costs, as well as streamlining data management activities for our data owners and stewards, such as data quality and metadata management automations within the platform.
WhyThis Job’s a Big Deal
As part of a small Data and Analytics team you will have the opportunity to perform a wide range of tasks and manage a modern data technology stack including Snowflake on AWS, Fivetran, dbt, Github, Power BI, and related integrations. You will be the point person for the configuration and operation of all the data platforms and tools, responsible for security administration, cost management, integration, monitoring, resiliency, Data Ops processes, MLOps processes, and automations using Python and SQL scripts.
You’ll also wear multiple hats on the team, backing up team members in their responsibilities including data engineering tasks and helping translate business needs into technical solutions consistent with enterprise architecture best practices. We value ownership and accountability while building our external products to be the best in the world for our customers. We need an innovator that will solve complex technical problems, drive new data initiatives and introduce positive change in a highly engaged, collaborative environment, helping us leverage the value of data for our customers, partners, and employees.
- Support and promote the company values, culture, and HR processes
- Establish technical standards, best practices, and architectural guidelines for data and analytics
- Provide thought leadership on emerging technologies, tools, and methodologies in data engineering, platform engineering, and analytics
- Mentor and develop team members in good data engineering principles and platform features, fostering technical growth and career development
- Ensure adherence to data governance, security, and compliance policies across all data and platform initiatives
- Champion a culture of collaboration, innovation, and high‑quality engineering practices
- Architect and maintain enterprise‑scale data pipelines, ingestion, storage, and transformation processes using Fivetran, dbt, and Github
- Implement and enforce data quality, lineage, observability, and certification processes with the platform
- Integrate metadata from across the platform to support data quality, metadata management, and end‑to‑end observability
- Integrate and automate activities and processes to help data architects and owners manage security approvals, retention, master data, metadata, and reference data policies
- Oversee deployment and operationalization of analytics, reporting, and machine learning platforms
- Monitor, support, and troubleshoot issues with data platforms, tools,…
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