Industrial Data Engineer - Lakehouse & ETL Architect

Vulcan Elements is manufacturing American rare-earth permanent magnets for a secure, resilient future. With a focus on national security and economic resiliency, we serve critical industries such as defense, aerospace, and automotive, powering a high-technology future. Vulcan Elements is building a team of ambitious professionals committed to Mission Focus, Technical Excellence, and Transparency.

As theData Engineer, you will design and build the data infrastructure that makes Vulcan’s operational and business data useful — first at pilot scale, and then as the foundation for a 10,000 ton/year facility. You will work from architecture to implementation: evaluating and selecting platforms, designing data models and pipelines, and building the systems that collect, contextualize, and deliver data to the teams and tools that depend on it.

You will collaborate closely with cross-functional stakeholders to translate operational requirements intoa durable, scalable data architecture. As Vulcan grows, this rolehas the opportunity toexpand into a team leadership position.

Responsibilities

• Design and own Vulcan’s data architecture from operational data stores through ETL pipelines to the analytics and AI layer
• Evaluate and select platforms for the data Lakehouse, ETL tooling, and operational databases, weighing scalability, compliance requirements, operational burden, and cost
• Review, refine, and implement data architecture design documents, ensuring designs are technically sound and account for CUI and ITAR data handling requirements
• Make and document key platform and design decisions with enough clarity that future team members can understand the reasoning and build on it
• Ensure the architecture scales from pilot plant to full-scale facility without fundamental redesign
• Apply sound engineering practices to everything you build:version control, testing, observability, and documentation,and hold those standards as the data team grows
• Design and build ETL pipelines that move data from operational data stores into the data Lakehouse with full contextual enrichment, making it ready for analytics and AI workloads
• Build reliable ingest paths for structured data, time-series data, files, images, and other outputs from manufacturing and lab systems
• Collaborate across engineering, operations, and IT to understand data flows, dependencies, and integration requirements, and translate them into pipeline and architecture decisions
• Identifyandeliminatemanual data workflows, replacing them with monitored, reliable pipelines
• Diagnose and resolve data quality issues across the stack, and build monitoring into pipelines so problems surface early

Data Modeling & Quality

• Define data models that support operational queries, analytical workloads, and future AI and ML applications
• Own data contextualization standards ensuring every data point carries the metadata needed to make it meaningful.
• Contribute to schema design and payload definitions for operational data stores, working toward consistency and legibility across the organization
• Support the development of reporting and visibility tools that give operations and leadership clear insight into process and quality data
• Write clear technical documentation for architecture decisions, data models, pipeline designs, and operational runbooks

Responsibilities and tasks outlined are not exhaustive and may change asdeterminedby the needs of the business.

Qualifications

• 8+ years of experience in data engineering, data infrastructure, or a closely related technical role witha track recordof owning and delivering production systems
• Demonstrated experience designing and building data lakes, Lake houses, or analytical data stores; understands the tradeoffs between platforms and can make and defend platform selection decisions
• Strong experience designing and building ETL/ELT pipelines that enrich and contextualize data
• Deep fluency with data modeling for both operational and analytical workloads; can design schemas that serve present needs without foreclosing future ones
• Experience with relational databases (Postgre
  
  SQL, SQL Server, or similar);writesand debugs SQL confidently
• Comfortable working in a…