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Enterprise Data Jobs (NOW HIRING)

The Director, Enterprise Data is responsible for building and leading the company's enterprise-wide data strategy to ensure data integrity, availability, and accessibility for advanced analytics and ...

S. Bank is seeking an experienced Enterprise Data Architect to define, lead, and evolve our enterprise-wide data architecture strategy. As a member of the Enterprise Architecture team, this role ...

They are seeking an experienced Enterprise Data Architect to define and lead their enterprise-wide data architecture strategy, collaborating with various teams to design scalable and secure data ...

Enterprise Data Architect Location: New Jersey, NYC, Dallas, TX/Charlotte, NC/Atlanta, GA /Chicago, IL Job Type: Full Time Must Have Technical/Functional Skills Enterprise Data Architect in Data ...

Enterprise Data Architect JOB SUMMARY As an Enterprise Data Architect, you are responsible for defining how data should be structured, integrated, and delivered across the organization to support ...

Enterprise Data Architect Location: Primary - NJ/NYC Secondary - Dallas/Charlotte/Atlanta/Chicago Fulltime Must Have Technical/Functional Skills Enterprise Data Architect in Data & Analytics will ...

Under the direction of Chief Data & Analytics Officer, the Enterprise Data Architect is a technical leader responsible for defining, documenting, and governing the canonical data model and ...

Enterprise Data Architect JOB SUMMARY As an Enterprise Data Architect, you are responsible for defining how data should be structured, integrated, and delivered across the organization to support ...

Enterprise Data Architect JOB SUMMARY As an Enterprise Data Architect, you are responsible for defining how data should be structured, integrated, and delivered across the organization to support ...

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Enterprise Data information

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How much do enterprise data jobs pay per hour?

As of May 31, 2026, the average hourly pay for enterprise data in the United States is $71.92, according to ZipRecruiter salary data. Most workers in this role earn between $62.50 and $82.45 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Enterprise Data professional, and why are they important?

To thrive as an Enterprise Data professional, you need a strong background in data management, analytics, and database technologies, often supported by a degree in computer science, information systems, or a related field. Familiarity with tools like SQL, Python, data warehousing platforms, ETL systems, and certifications such as CDMP or AWS Data Analytics are typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for translating business needs into data solutions. These skills ensure the integrity, accessibility, and strategic use of data to drive business insights and decision-making.

How does an Enterprise Data professional typically collaborate with other departments within an organization?

Enterprise Data professionals regularly work with cross-functional teams, including IT, business analysts, and department heads, to ensure data is accurately collected, integrated, and leveraged for business insights. This collaboration often involves understanding departmental data needs, translating business requirements into technical solutions, and facilitating data governance practices. Effective communication and coordination are key, as these professionals help bridge the gap between technical data management and business objectives, ensuring data-driven decision-making across the organization.

What is an Enterprise Data professional?

An Enterprise Data professional is responsible for managing, organizing, and securing the large volumes of data generated and used by a business or organization. Their role typically involves developing data strategies, ensuring data quality, integrating various data sources, and supporting data governance initiatives. They work to ensure that data is accessible, reliable, and used effectively to drive business decisions across the enterprise. These professionals often collaborate with IT, data analysts, and business leaders to align data management practices with organizational goals.

What is the difference between Enterprise Data vs Data Analyst?

AspectEnterprise DataData Analyst
Required CredentialsBachelor's or higher in Data Science, Computer Science, or related fields; certifications like CDMP or DAMA often preferredBachelor's in Statistics, Data Science, or related; certifications like Microsoft Data Analyst Associate common
Work EnvironmentTypically within large organizations managing enterprise-wide data systemsOften in various industries analyzing data sets to generate reports and insights
Employer & Industry UsageUsed by corporations to manage and govern enterprise data assetsEmployed across industries to interpret data and support decision-making

Enterprise Data professionals focus on managing and governing large-scale organizational data systems, ensuring data quality and compliance. Data Analysts interpret data to provide actionable insights, often working on specific projects or departments. While both roles require strong analytical skills, Enterprise Data roles emphasize data infrastructure and strategy, whereas Data Analysts focus on data interpretation and reporting.

More about Enterprise Data jobs
Infographic showing various Enterprise Data job openings in the United States as of May 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $149,587 per year, or $71.9 per hour.
Enterprise Data Architect

Full-time

Posted 16 days ago


Steel Dynamics rating

7.8

Company rating: 7.8 out of 10

Based on 57 frontline employees who took The Breakroom Quiz

161st of 512 rated manufacturers


Job description

Steel Dynamics

The Enterprise Data Architect is the technical cornerstone of Steel Dynamics' enterprise data platform initiative. This newly created role will lead the design and build-out of a company-wide data platform that will serve as SDI's first foundation for enterprise reporting, analytics, and AI/ML.

SDI is a highly decentralized organization. Divisions own their source systems and operate with significant autonomy. The Enterprise Data Architect must be equally comfortable working independently to drive the architecture forward and collaboratively to bring divisions along. The role requires earning trust across divisions rather than relying on positional authority.

This role begins as a senior individual contributor with significant build-out responsibility, and is expected to evolve as the platform matures and the enterprise data function grows. The strongest candidates will be excellent as both architects and builders.

What Makes This Role Distinctive

  • Greenfield enterprise platform with growth trajectory. This is a build-from-the-ground-up opportunity. Architectural choices made in this role will shape SDI's data foundation for the next decade, and the role is structured to evolve as the platform matures and the enterprise data function grows.
  • Real architectural authority. SDI has not locked in technology commitments for this platform. The Enterprise Data Architect's recommendations on platform, tooling, and standards will drive the decisions.
  • Builder-leader trajectory. This role is positioned to play a central part in shaping and growing SDI's enterprise data engineering capability over time.
  • A culture that moves fast when aligned. SDI is decentralized, but when we align, we move with surprising speed. A successful architect here will see their designs translated into operating reality faster than in most enterprise environments.

About Steel Dynamics, Inc.

Steel Dynamics is one of the largest domestic steel producers and metals recyclers in North America, with approximately 15,000 employees and operations spanning steelmaking, steel fabrication, metals recycling, aluminum, and biocarbon. SDI's culture is built on entrepreneurial spirit, decentralized decision-making, accountability, and aligned long-term interests across all stakeholders. We are committed to safety, operational excellence, and continuous innovation.


  • Lead the design and build-out of the enterprise data platform, including platform selection, reference architecture, and the standards and patterns the platform will operate on.
  • Define the architecture for moving data from divisional source systems — predominantly on-premises SQL Server — into the cloud-hosted platform, including ingestion, security, and reliability.
  • Establish enterprise data engineering standards governing the corporate-owned platform.
  • Partner with divisional IT teams on integrating division data into the platform, providing architectural guidance and technical support without taking ownership of divisional data away from the divisions.
  • Provide hands-on data engineering support to divisions that do not yet have dedicated data engineering capability; transition this work to a growing team as the function scales.
  • Design the security, governance, and access-control model for the platform.
  • Architect the platform to support enterprise AI and machine learning workloads.
  • Define environment, CI/CD, cost management, and operational monitoring approaches for the platform.
  • Serve as the senior technical voice in vendor evaluations, proof-of-concept work, and platform decisions.
  • Mentor divisional data engineers and analysts working within the platform.
  • Communicate clearly with non-technical executive stakeholders, translating architectural choices into business outcomes, risks, and trade-offs.

Required

  • 10+ years of progressive experience implementing large-scale software systems in production enterprise environments.
  • 5+ years experience in data engineering, data warehousing, and/or data architecture in production environments.
  • Demonstrated experience leading and personally owning the design and delivery of at least one greenfield or major-overhaul enterprise data platform spanning multiple business units, source systems, or geographies.
  • Demonstrated experience designing hybrid cloud / on-premises data architectures, including secure and reliable movement of data from on-premises source systems into cloud platforms.
  • Working proficiency across multiple cloud data platforms sufficient to lead a credible platform evaluation and make defensible recommendations.
  • Strong familiarity with the Microsoft data and analytics ecosystem.
  • Strong technical foundation across SQL, a general-purpose programming language used in data engineering, modern data engineering practices, and data warehousing fundamentals.
  • Experience integrating data from heterogeneous source systems in a multi-business-unit environment, including ERP and operational systems.
  • Working knowledge of data security, governance, and compliance frameworks sufficient to architect compliant data platforms.
  • Excellent written and verbal communication skills, with proven ability to present architectural concepts and trade-offs to both technical teams and non-technical executive stakeholders.
  • Demonstrated ability to work effectively in a decentralized organizational structure — building consensus, earning trust, and driving outcomes through influence rather than authority.
  • Bachelor's degree in a relevant field, or equivalent professional experience.

Preferred

  • Experience designing data platforms in manufacturing, metals, industrial, or other heavy-asset industries.
  • Experience integrating MES, historian, and shop-floor data alongside ERP and financial data.
  • Experience architecting data platforms that support AI/ML and large language model workloads.
  • Experience leading or mentoring distributed data engineering teams.
  • Experience establishing data governance practices in decentralized, multi-business-unit organizations.

Steel Dynamics, Inc., and all affiliated entities are equal opportunity employers. 


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About Steel Dynamics

Sourced by ZipRecruiter

Steel Dynamics is one of the largest and most diversified domestic steel producers and metals recyclers in the United States, with an estimated steelmaking and coating capacity of approximately 13 million tons, and facilities located throughout the United States and in Mexico. We operate using a circular manufacturing model, producing lower-carbon-emission, quality steel using electric arc furnace (EAF) technology with recycled ferrous scrap as the primary input. Our circular economy is powered by our three primary operating platforms: steel, metals recycling, and steel fabrication. Our steel operations produce steel products, including hot roll, cold roll, and coated sheet steel, structural steel beams and shapes, rail, engineered special-bar-quality steel, cold finished steel, merchant bar products, and specialty steel sections. Our metals recycling operations collect and process ferrous and nonferrous scrap from manufacturing and end-of-life items, such as automobiles, appliances, and machinery. This processed scrap is then sold to end-users for reuse, including our EAF steel mills, which produce new steel from the scrapped material. We sell a meaningful amount of steel to our own steel fabrication operations that in turn produce and sell structural steel joist and deck building systems to consumers.

Industry

Manufacturing

Company size

5,001 - 10,000 Employees

Headquarters location

Fort Wayne, IN, US

Year founded

1993