Data Architect

About Niron

Niron Magnetics is commercializing the first new magnetic material in decades powered by its breakthrough material formulation and advanced manufacturing process. The company’s proprietary magnet technology based on Iron Nitride enables magnets that are inherently high magnetization, free of rare earths and other critical materials, and solve supply chain reliability challenges, will drive innovation in various industries. Headquartered in Minneapolis, MN, Niron Magnetics is comprised of a team of professionals with a desire to make a positive impact on the global community. We were named one of “America's Top GreenTech Companies” for 2024 and 2025 by TIME Magazine and the “Innovation of the Year” at the 2025 mHUB Fourth Revolution Awards.

Our team is made up of people who think big, dare to innovate, and strive to impact the planet through technological innovation for our customers. Ready to work alongside amazing people, solve complex problems, and leave a legacy? Join our team.

What you’ll do

Niron Magnetics is seeking a Enterprise Data Architect to define and evolve the data architecture that underpins manufacturing, R&D, and business operations as we scale toward high-volume production This role owns how the estate matures from the current MS fabric foundation, scaling and expanding the platform, and evaluating and deploying additional environment in the data estate as well as complementary data tools as the business requires.

This is a senior, hands-on technical leadership role for someone excited to scale and mature a foundational data platform in a high-growth, deep-tech manufacturing environment operating under strict compliance requirements.

Define Data Architecture and Strategy

• Design and own the end-to-end enterprise data architecture spanning ingestion, storage, modeling, transformation, governance, and consumption.
• Build on the existing Microsoft Fabric platform and initial data lakehouse, maturing the architectural patterns, standards, and reference designs that make the estate scalable, secure, and maintainable.
• Assess where the current lakehouse foundation should expand, and evaluate, select, and deploy additional data estate stores, and complementary data tooling to meet analytics, reporting, and AI needs across the business.
• Define canonical data models, master data management, and semantic layers that create a single, trusted source of truth across the business.
• Set the roadmap for evolving the data estate as Niron scales, sequencing work to deliver near‑term value while protecting long‑term architectural integrity.

Enable Analytics, Reporting, and AI

• Partner with Manufacturing, R&D, Quality, Finance, and Operations to identify high-value data and analytics use cases (e.g., production reporting, yield and quality analysis, cost and supply insights).
• Build the data foundations that power business intelligence, self‑service analytics, and downstream AI/ML systems.
• Design robust integration between core systems—ERP (D365 Finance & Operations), MES/manufacturing systems, laboratory tools, and enterprise SaaS—via APIs, message queues, and ETL/ELT pipelines.
• Translate business and technical requirements into resilient, well‑documented data designs.

Data Governance, Security, and Compliance

• Own data governance: data quality, lineage, cataloging, classification, retention, and access control.
• Partner with IT and Security to ensure the data estate meets reliability, security, and regulatory compliance obligations, including handling of controlled and export‑regulated data.
• Design data segregation and controls appropriate to a multi‑tenant, compliance‑sensitive environment.

Technical Leadership and Collaboration

• Act as the technical authority and advisor on data architecture, best practices, and trade‑offs.
• Review designs, mentor data and analytics engineers, and raise the technical bar across teams.
• Support build‑vs‑buy decisions and evaluate vendors, tools, and platforms.
• Communicate complex technical concepts clearly to non‑technical stakeholders and influence without authority.

What We’re Looking For

• 10+ years of experience in data engineering, data platforms, or enterprise/data architecture, with demonstrated architectural ownership of production systems.
• Deep expertise designing modern data estate architecture, dimensional and canonical data modeling, and semantic layers.
• Deep hands‑on experience with a modern cloud data platform, specifically Microsoft Fabric and the Azure data stack experience.
• Experience with Databricks, specifically in a controlled‑data environment, is strongly desired.
• Demonstrated experience integrating enterprise systems and building data pipelines via REST, GraphQL, message queues, webhooks, and ETL/ELT tooling.
• Strong grounding in cloud architecture (Azure preferred), and in data governance disciplines—quality, lineage, cataloging, MDM, and access control.
• Proficiency in SQL and Python; familiarity with R and/or Spark a plus.
• Experience integrating with or sourcing data from ERP (D365 F&O or comparable) and operational/industrial systems preferred.
• Ability to balance near‑term delivery with long‑term architectural vision.
• Excellent communication skills and comfort operating in ambiguous, early‑stage environments.

Nice to Have

• Experience in manufacturing, industrial, or deep‑tech environments.
• Experience working within a regulated or a compliance‑driven environment.
• Advanced degree in Computer Science, Engineering, Data Science, or a related field.
• Experience with time‑series, OT/sensor, or manufacturing process data.
• Familiarity with enabling AI/ML and RAG workloads on top of a governed data estate.
• Passion for clean tech, sustainable materials, or climate‑positive innovation.

Our pay and benefits

• Salary $165,000–$190,000
• Equity position in Niron via stock option grant
• Comprehensive medical, dental, and vision insurance
• Mental healthcare
• 401k plan with company match
• Paid vacation, sick time, and holidays
• Experience in a fun, high‑performing, manufacturing environment