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Enterprise Data Jobs (NOW HIRING)

Steampunk

Enterprise Data Architect

Mclean, VA · Remote

We are seeking an Enterprise Data Architect to guide the design, development, and governance of enterprise data architectures across complex mission environments. This role combines hands-on ...

Steampunk

Enterprise Data Architect

Mclean, VA · Remote

$135K - $165K/yr

Overview We are seeking an Enterprise Data Architect to guide the design, development, and governance of enterprise data architectures across complex mission environments. This role combines hands-on ...

OU Medical Center

Enterprise Data Architect

Enterprise Data Architect Department: ETS Analytics and AI Data This position may be performed remotely from the following locations within the United States of America: Arkansas, Kansas, Missouri ...

OU Health

Enterprise Data Architect

Enterprise Data Architect Department: ETS Analytics and AI Data This position may be performed remotely from the following locations within the United States of America: Arkansas, Kansas, Missouri ...

Steampunk

Enterprise Data Architect

Mclean, VA · On-site

$135K - $165K/yr

Overview We are seeking an Enterprise Data Architect to guide the design, development, and governance of enterprise data architectures across complex mission environments. This role combines hands-on ...

OU Health

Enterprise Data Architect

Enterprise Data Architect Department: ETS Analytics and AI Data This position may be performed remotely from the following locations within the United States of America: Arkansas, Kansas, Missouri ...

Peraton

Enterprise Data Architect

Herndon, VA · On-site

Herndon, VA Defines enterprise data architecture, canonical data models, aviation data exchange standards compliance, data integration patterns, data governance frameworks, and cross-package data ...

Socket.dev

NY · On-site

Summary The Enterprise Data Manager & Architect is responsible for defining, governing, and optimizing how WellDyne identifies, structures, secures, and manages data across transactional, operational ...

Peraton

Enterprise Data Architect

Herndon, VA · On-site

$112K - $179K/yr

Herndon, VA Defines enterprise data architecture, canonical data models, aviation data exchange standards compliance, data integration patterns, data governance frameworks, and cross-package data ...

Peraton

Enterprise Data Architect

Herndon, VA · On-site

Herndon, VA Defines enterprise data architecture, canonical data models, aviation data exchange standards compliance, data integration patterns, data governance frameworks, and cross-package data ...

Peraton

Enterprise Data Architect

Herndon, VA · On-site

Herndon, VA Defines enterprise data architecture, canonical data models, aviation data exchange standards compliance, data integration patterns, data governance frameworks, and cross-package data ...

Koantek

Enterprise Data Architect

Milwaukee, WI

Enterprise Data Architect Primary Purpose Responsible for designing and architecting data/MDM solutions, analyzing, implementing, and deploying these solutions both on-premises and in the cloud. By ...

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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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What job categories do people searching Enterprise Data jobs look for?

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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 Architect Consultant

Houston, TX • On-site

CG Infinity
IT Services • 201 - 500 employees
Learn more about CG Infinityexternal

Other

Re-posted 6 days ago

Job description

Enterprise Data Architect Consultant Position Summary

CG Infinity is seeking a strategic and hands‑on Enterprise Data Architect to design, build, and lead the implementation of a scalable, enterprise‑wide data Lakehouse. This role will be responsible for developing a modern data architecture from the ground up, integrating multiple systems and business units into a unified data ecosystem that drives analytics, reporting, and business decision‑making.

The ideal candidate combines deep technical expertise with strong business acumen, capable of leading discovery efforts, defining priorities, and ensuring data solutions are aligned with organizational goals. This individual will also play a key leadership role in establishing data governance, master data management (MDM), and enterprise data standards.

Key Responsibilities Enterprise Data Architecture & Strategy
  • Design and implement a scalable, secure, and high‑performance enterprise data Lakehouse from inception.
  • Define the end‑to‑end data architecture, including data ingestion, transformation, storage, integration, and consumption layers.
  • Establish architectural standards, frameworks, and best practices aligned with business and technology strategies.
  • Evaluate and recommend technologies (cloud platforms, ETL/ELT tools, data lakes, Lakehouses) to support long‑term scalability.
Cross‑Functional Discovery & Requirements Alignment
  • Lead discovery sessions with business and technical stakeholders to identify high‑value use cases, priorities, and dependencies.
  • Translate business requirements into technical data models, data flows, and architecture designs.
  • Ensure alignment between data solutions and business objectives, including KPIs, reporting, and analytics needs.
  • Develop and maintain a data roadmap with clearly defined phases, milestones, and deliverables.
Data Lakehouse Development & Delivery
  • Oversee development of integrated data pipelines that connect disparate systems (ERP, CRM, operational systems, third‑party platforms).
  • Define and implement data models (conceptual, logical, physical) to support analytics and reporting.
  • Establish data quality frameworks and ensure reliability, consistency, and integrity of enterprise data.
  • Ensure performance optimization and scalability of the data environment.
Data Governance & Master Data Management
  • Develop and implement enterprise data governance policies, standards, and controls.
  • Lead Master Data Management (MDM) initiatives to standardize key business entities across systems.
  • Define data ownership, stewardship, and accountability models across business units.
  • Ensure compliance with regulatory, security, and data privacy requirements.
Leadership & Stakeholder Engagement
  • Act as a trusted advisor to executive leadership, including the CTO and business leaders.
  • Communicate complex technical concepts clearly to non‑technical stakeholders.
  • Lead cross‑functional teams, including data engineers, analysts, and business users.
  • Drive adoption of data solutions across the organization through change management and stakeholder alignment.
Required Qualifications
  • 8+ years of experience in data architecture, data engineering, or enterprise data management roles.
  • Proven experience building an enterprise data Lakehouse from scratch spanning multiple systems and business units.
  • Strong experience with data modeling, ETL/ELT design, and data integration frameworks.
  • Hands‑on experience with cloud data platforms (e.g., Azure, AWS, or GCP).
  • Demonstrated expertise in:
    • Python Development
    • Data Governance frameworks
    • Master Data Management (MDM)
    • Data quality and metadata management
  • Experience leading discovery sessions and requirements gathering workshops with senior stakeholders.
  • Strong understanding of enterprise systems (ERP, CRM, operational apps) and integration patterns.
  • Excellent communication, facilitation, and leadership skills.
Preferred Qualifications
  • Experience in consulting environments or multi‑client, multi‑business unit organizations.
  • Industry experience in oil & gas or chemical sectors, with an understanding of upstream, midstream, downstream, or refining operations.
  • Familiarity with modern data tools (e.g., Snowflake, Databricks, Azure Synapse, Power BI, Tableau).
  • Experience implementing data lakes, Lakehouse architectures, or hybrid data ecosystems.
  • Knowledge of Agile and iterative delivery methodologies.
  • Relevant certifications (e.g., Azure Data Architect, AWS Data Analytics, DAMA CDMP).
Success Metrics
  • Successful delivery of a fully operational enterprise data Lakehouse aligned with business priorities.
  • Measurable improvement in data accessibility, quality, and reporting capabilities.
  • Adoption of data governance and MDM practices across business units.
  • Delivery of a clear project roadmap with defined milestones, timelines, and outcomes.
  • Positive stakeholder feedback on alignment between business needs and technical solutions.
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