Data Engineer

MP Materials Corp.•Fort Worth, TX

About The Position

MP Materials (NYSE: MP) is rebuilding American industrial capability for a new era of autonomy, robotics, and electrification. We are the only U.S. company with a fully integrated rare earth supply chain—from mining and refining to advanced metal and magnet manufacturing. Our products include both the critical materials used to make permanent magnets and the finished magnets themselves—enabling next-generation technologies in robotics, automation, aerospace, transportation, defense, and energy systems. These materials are the foundation of physical AI—the convergence of computation, movement, and control. We hire ambitious, mission-driven people who want to tackle complex challenges and shape the future of strategic industries. Our culture is rooted in teamwork, resiliency, and integrity, with a deep commitment to operational excellence and national purpose. MP is rapidly evolving from a materials producer into a leading U.S. manufacturer—and our people are driving that transformation. The Data Engineer will design, build, and operationalize high-quality data pipelines and data products that integrate OT (Operational Technology) and IT (Information Technology) sources. This role partners closely with business stakeholders and data stewards to enable analytics, reporting, and AI use cases across domains such as Mining, manufacturing, Operations, Supply Chain, HR and Finance. Incidental travel may be required for collaboration and on-site system understanding.

Requirements

Bachelor’s / Master’s in Computer Science, Information Systems, or related field.
3+ years of experience in data engineering (5+ preferred), ideally in Azure cloud environments. Proficiency with SQL, Python, PySpark, and data-modeling concepts.
Experience with Microsoft Fabric, Azure Synapse, Azure Data Factory.
Experience with Azure cloud service: Compute, Database, Integration, Storage, Security, DevOps.
Familiarity with industrial / OT data systems (e.g., AVEVA PI System, SCADA, historian data).
Knowledge of data governance and lineage tools (e.g., Microsoft Purview).
Strong collaboration and communication skills to work with both business and technical stakeholders.

Nice To Haves

Experience in building domain-oriented data products or working within a data mesh architecture.
Experience with Azure cloud service: Compute, Database, Integration, Storage, Security, DevOps.
Exposure to Power BI, Databricks, or Snowflake.
Experience with CI/CD for data pipelines using Azure DevOps or GitHub Actions.
Industrial, energy, or manufacturing domain knowledge.

Responsibilities

Design and implement data ingestion, transformation, and curation pipelines across OT and IT sources (e.g., AVEVA PI, SAP, SQL Server, Azure Synapse/Fabric, MS 365).
Build reusable, governed data products in Microsoft Fabric /Synapse, Azure Data Factory for domain[1]specific analytics.
Work with business data owners to translate use-case requirements into robust data models.
Implement data quality monitoring, lineage tracking, and semantic documentation to align with governance standards.
Collaborate with Data Platform Engineers and infrastructure teams to optimize pipeline performance, storage, and compute usage.
Support self-service analytics through curated datasets and Power BI semantic models.
Document technical designs, lineage, and business logic for data products.
Contribute to data security and controlled access patterns in coordination with governance frameworks.
Participate in sprint ceremonies and agile delivery of data solutions.
Other duties as assigned.