Data Architect

MIDREX TECHNOLOGIES INC•Charlotte, NC

1d•Hybrid

About The Position

At Midrex, you will do work that matters alongside people who believe you matter. The work won’t be easy, but it will be worth it. You’ll be part of a great team—with plenty of autonomy—to bring out your best. And you’ll be well compensated and have a best-in-class benefits package. Since 1987, Midrex has been the world leader in direct reduction technology, offering the best proven method for decarbonization in the iron and steel industry available today. Our rapid growth is transforming the steel industry and our planet. And none of it would be possible without our people, who bring vision, compassion, and extraordinary expertise to this work every day. So, if you’re looking to do big work in a small-team environment, Midrex is just the place for you. We are seeking a highly skilled and strategic Data Architect to support the development and implementation of our enterprise data strategy, governance framework, and supporting technical architecture. This role will be instrumental in shaping how our organization manages, leverages, and protects data as a strategic asset to drive innovation, improve decision-making, and support revenue diversification. In this role you will collaborate with Digitial Service and Solutions, department teams, analytics teams, and external partners to define and deliver scalable data solutions, ensuring the alignment of data architecture with business goals and compliance requirements.

Requirements

Expertise in cloud data platforms (e.g., AWS, Azure, GCP), data modeling, and data warehousing (e.g., Snowflake, Redshift, BigQuery).
Strong knowledge of data governance frameworks (e.g., DAMA-DMBOK, DCAM), data privacy standards (e.g., GDPR, CCPA), and security best practices.
Experience with modern data tools such as dbt, Kafka, Airflow, Informatica, Talend, or similar.
Excellent communication and stakeholder engagement skills.
Strong organizational skills and ability to work on multiple tasks simultaneously under time sensitive deadlines.
Bachelor’s degree or higher in Computer Science, Information Systems, Data Science, or related field.
6+ years of experience in data architecture, data engineering, or enterprise information management.
Proven track record designing enterprise data solutions in complex, multi-system environments.

Nice To Haves

Experience in engineering organizations and global enterprise environments.
Familiarity with data mesh, data fabric, or decentralized data architectures.
Certification in cloud architecture (AWS/Azure/GCP), data governance, or TOGAF.
Experience working with small to mid-sized organizations.
Experience around organizing IIoT and OT level data modeling.

Responsibilities

Design and evolve the enterprise data architecture to support business strategy and digital transformation initiatives.
Define the roadmap for data platforms, including data lakes, data warehouses, pipelines, and APIs.
Ensure the architecture supports scalability, interoperability, and performance across analytics, applications, and operational systems.
Partner with business and compliance stakeholders to design and implement a comprehensive data governance framework.
Define data ownership, stewardship, metadata standards, and data quality rules.
Establish and maintain data catalogs and lineage documentation.
Lead the selection, design, and implementation of modern data platforms (cloud or hybrid), including integration tools, ETL/ELT pipelines, MDM, and data security technologies.
Collaborate with SysOps and security teams to ensure secure, resilient, and cost-effective infrastructure.
Translate business needs into enterprise data models, logical/physical data designs, and scalable pipelines.
Define standards, patterns, and best practices for data modeling, ingestion, transformation, and access.
Support use case delivery (e.g., analytics, AI/ML, BI, regulatory reporting) through design guidance and hands-on architecture.
Act as the data strategy thought partner to executive and operational stakeholders.
Mentor data analysts, and teammates on architectural and governance standards.
Advocate for data literacy and responsible data practices across the organization.