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Enterprise Data Jobs (NOW HIRING)

Prophecy Technologies

Enterprise Data Architect

The Enterprise Data Architect will provide leadership to accelerate strategic initiatives, integrations, modernization programs, and innovation projects. This involves designing scalable data ...

Nastech Global

Enterprise Data Architect

New York, NY · On-site

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 ...

Sarian, Inc.

Enterprise Data Architect

Jersey City, NJ · On-site

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 ...

Apptad, Inc.

Enterprise Data Architect

Sacramento, CA · On-site

Enterprise Data Architect Location: Sacramento, CA (1-2 Days Hybrid/ weekly) Job Type: Long term contract Project Description We are seeking a highly experienced Enterprise Data Architect to support ...

OU Medicine

WI · On-site

## Enterprise Data ArchitectApplylocations: Virtualtime type: Full timeposted on: Posted Todayjob requisition id: R0063293## **Position Title:**Enterprise Data Architect## **Department:**ETS Analytics ...

Sarian, Inc.

Enterprise Data Architect

Atlanta, GA · On-site

Must Have Technical/Functional Skills Enterprise Data Architect in Data & Analytics will play a key role in driving solution architecture design, evaluation, and selection, buy vs. build decisions ...

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Enterprise Data information

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How much do enterprise data jobs pay per hour?

As of Sep 13, 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 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 are the key skills and qualifications needed to thrive as an enterprise data professional?

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 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.

What does an enterprise data analyst do?

An enterprise data analyst collects, analyzes, and interprets large datasets to help organizations make data-driven decisions. They use tools like SQL, Excel, and data visualization software to identify trends, create reports, and support strategic planning. Strong analytical skills and knowledge of data management are essential for this role.
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Enterprise Data jobs near you
Infographic showing various Enterprise Data job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $149,587 per year, or $71.9 per hour.

Enterprise Data Archtect

Harrisburg, PA • On-site

MJDP Resources
See more jobs at MJDP Resourcesexternal

Full-time

Re-posted 3 days ago

Job description

The Enterprise Data Architect is responsible for defining and evolving the enterprise information architecture and reusable data products to support transformation and AI priorities.

This role partners with business leaders, product and engineering teams and enterprise technology org to identify which information assets should be shared across agencies and which should remain domain specific. The position will define data domains, create data models, ensure data quality, map source to domain and assist in creating contracts to support modernization initiatives and future AI capabilities. The role serves as the bridge between business processes and technical implementation, ensuring that new solutions contribute to a sustainable enterprise data foundation rather than creating additional silos. The ideal candidate possesses a comprehensive understanding of data architecture principles, practical data modeling experience, and deep expertise in data-centric architecture.

Key Responsibilities

Enterprise Information Architecture

  • Define conceptual and logical data models for common business entities.
  • • Establish canonical models and enterprise information standards.

• Define relationships between enterprise and domain-specific data assets.

• Design enterprise information architecture that incorporates data classification, privacy, security, and regulatory requirements by design.

Modernization Programs

• Partner with workflow modernization teams (product and engineering) to embed reusable data products into solution designs.

• Analyze legacy systems and identify information assets suitable for enterprise reuse.

• Prevent duplication of data structures across applications and agencies.

• Support data migration strategies and target-state architecture.

Data Product Architecture

• Identify and support design of reusable data products

• Define schemas, interfaces, metadata and quality requirements

• Establish product boundaries, stewardship and ownership models.

Data Governance and Metadata

• Establish data architecture principles, data standards, best practices, and guidelines including data catalog, data lineage, observability, security and interoperability

• Define business definitions and data quality expectations.

Platform and Technology Collaboration

• Work with engineering and platform teams to translate business concepts into technical designs.

• Partner with cloud, integration and data teams to implement enterprise data products.

• Promote API-first and product-based approaches to information sharing.

AI Enablement

• Ensure enterprise data products are discoverable, governed and suitable for future AI use cases.

• Support semantic layers, knowledge graphs and natural language access to enterprise information.

  • Desired Background and Experience

• Bachelor of Computer Science, Information Systems, Systems Programming or equivalent combination of relevant education and experience

• Minimum 10 years of experience in data architecture, information architecture or enterprise architecture.

• 8+ years of hands-on experience in data architecture, data engineering, or advanced database design, modeling experience in designing or implementing data warehouse/data marts, MDM concepts and tools

• At least 5+ years of experience with data platforms such as Snowflake, Databricks, MongoDB and big data on cloud-based ecosystems (AWS, Azure, GCP). Experience working with unstructured data is a plus.

• Experience working with data security, privacy and regulatory requirements for handling sensitive data

• Experience in designing and implementing data quality initiatives, including platforms and tooling

• Demonstrable experience supporting large-scale modernization or digital transformation initiatives across multiple domains and stakeholders

• Ability to work across domains and stakeholders with strong communication skills

• Proven ability to develop work plans for self, resolve ambiguity and lead teams without authority

  • Industry Experience in Public sector, Healthcare or Financial Services is preferable

    Candidates may have previously served as Principal Architect, Enterprise Information Architect, Solution Architect for large enterprises or modernization initiatives