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Technology Operations Enterprise Data Strategy Jobs in Washington, DC

... operational performance, and support the delivery of resilient, secure, and scalable technology ... Develop hybrid cloud strategy * Manage enterprise data strategy * Lead data governance initiatives

... data that automates operations and delivers a trusted, comprehensive view of the enterprise for reporting and decision-making. Strategic priorities are set by the Head of Enterprise IT; the Sr. ...

... data that automates operations and delivers a trusted, comprehensive view of the enterprise for reporting and decision-making. Strategic priorities are set by the Head of Enterprise IT; the Sr. ...

This role connects business priorities, technology investments, analytics, AI, and enterprise data capabilities to ensure data is used as a strategic asset. Working with executive leadership ...

... analytics, AI/ML, operational applications, and enterprise integration needs. * Develop and ... Lead integration strategy across platforms, including API-driven data access, streaming and event ...

Enterprise Data Architect

Mclean, VA ยท Remote

$135K - $165K/yr

... analytics, AI/ML, operational applications, and enterprise integration needs. * Develop and ... Lead integration strategy across platforms, including API-driven data access, streaming and event ...

Enterprise Data Architect

Mclean, VA ยท On-site

$135K - $165K/yr

... analytics, AI/ML, operational applications, and enterprise integration needs. * Develop and ... Lead integration strategy across platforms, including API-driven data access, streaming and event ...

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Technology Operations Enterprise Data Strategy information

See Washington, DC salary details

$29

$81

$103

How much do technology operations enterprise data strategy jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for technology operations enterprise data strategy in Washington, DC is $81.45, according to ZipRecruiter salary data. Most workers in this role earn between $70.77 and $93.37 per hour, depending on experience, location, and employer.

What is Technology Operations Enterprise Data Strategy?

Technology Operations Enterprise Data Strategy refers to the planning, management, and implementation of data-related processes and technologies across an organization to support its operational goals. This role involves setting standards for data governance, ensuring data quality, and aligning data initiatives with business objectives. Professionals in this field work to optimize data flow, storage, and security, enabling better decision-making and efficiency. They often collaborate with IT, business units, and data analytics teams to ensure data assets are leveraged effectively across the enterprise.

How does a Technology Operations Enterprise Data Strategy professional typically collaborate with other departments within an organization?

Professionals in Technology Operations Enterprise Data Strategy work closely with multiple departments, such as IT, business analytics, compliance, and executive leadership. They often facilitate communication between technical teams and business stakeholders to ensure that data initiatives align with organizational goals. This role involves coordinating data governance policies, integrating new technologies, and supporting data-driven decision-making across the enterprise. Successful collaboration requires strong communication skills and a deep understanding of both technical and business perspectives.

What are the key skills and qualifications needed to thrive in Technology Operations Enterprise Data Strategy, and why are they important?

To excel in Technology Operations Enterprise Data Strategy, you need strong expertise in data management, analytics, and strategic planning, often backed by a degree in computer science, information systems, or a related field. Familiarity with data warehousing solutions, ETL tools, data governance frameworks, and certifications like CDMP or AWS Certified Data Analytics is highly valuable. Exceptional problem-solving, stakeholder management, and communication skills help drive cross-functional initiatives and align data strategies with business goals. These competencies ensure effective data-driven decision making, operational efficiency, and long-term organizational success.

What is the difference between Technology Operations Enterprise Data Strategy vs Data Analyst?

AspectTechnology Operations Enterprise Data StrategyData Analyst
CredentialsTypically requires a degree in IT, Data Science, or related fields; certifications like CDMP or CBIP are commonRequires a degree in Statistics, Data Science, or related fields; certifications like Microsoft Data Analyst Associate or Tableau Desktop Specialist are common
Work EnvironmentFocuses on strategic planning, data governance, and infrastructure within enterprise IT teamsFocuses on data collection, analysis, and reporting to support business decisions
Employer & Industry UsageUsed in large organizations managing enterprise data assets and IT operationsUsed across industries for data reporting, visualization, and insights

While Technology Operations Enterprise Data Strategy professionals focus on aligning data initiatives with business goals and managing data infrastructure, Data Analysts primarily analyze data to generate actionable insights. Both roles require strong analytical skills but differ in scope and strategic involvement.

Infographic showing various Technology Operations Enterprise Data Strategy job openings in Washington, DC as of August 2026, with employment types broken down into 86% Full Time, and 14% Contract. Highlights an 100% In-person job distribution, with an average salary of $169,422 per year, or $81.5 per hour.

Manager, Data Strategy and Governance Office

National-Cooperative-Bank

Arlington, VA โ€ข On-site

$180 - $250/hr

Other

Posted 26 days ago


Key responsibilities

  • Lead the development, execution, and continuous improvement of the Bank's enterprise data strategy and operating model.

  • Oversee the Bank's enterprise data governance and information management programs, including policies, standards, and compliance monitoring.

  • Manage the Bank's Data Product Owner function, ensuring data products deliver measurable business value and support strategic initiatives.


Job description

Head of Enterprise Data Strategy and Governance

Job Category: Banking

Requisition Number: HEADO001528

  • Posted : August 4, 2026
  • Full-Time
  • Hybrid
Locations

Showing 1 location

VA Office
2011 Crystal Drive
Suite 800
Arlington, VA 22932, USA

VA Office
2011 Crystal Drive
Suite 800
Arlington, VA 22932, USA

Role Description Summary
The Head of Enterprise Data Strategy and Governance leads the Bank's enterprise data and AI strategy, and oversees governance of data, context, and AI assets. While reporting to the CIO, responsibilities will include enterprise data and AI architecture, data product and quality management, enterprise content management, information lifecycle management, and AI data enablement programs. This leadership role establishes and executes a comprehensive strategy to ensure that data and information assets are trusted, governed, secure, accessible, and leveraged to support strategic growth, operational excellence, regulatory compliance, innovation, and informed decision-making.


This role serves as the Bank's leader for enterprise data management and governance practices, partnering closely with business and technology leaders to maximize the value of data and information assets. The position is responsible for defining the enterprise data vision, guiding modernization of the Bank's data ecosystem, advancing data products and analytics capabilities, enabling responsible AI adoption through effective data management practices, and ensuring alignment with business objectives, risk management standards, and regulatory expectations.


Role Responsibilities:


Enterprise Data Strategy and Leadership
โ€ข Accountable for developing, executing, measuring, and continuously evolving the Bank's enterprise data strategy and associated operating model.
โ€ข Establish goals, objectives, governance structures, key performance indicators, operating procedures, and communications frameworks for the Data Strategy and Governance Office (DSGO).
โ€ข Lead strategic and operational planning for enterprise data, information management, analytics, governance, and content management capabilities.
โ€ข Identify opportunities to leverage data and information assets to improve business performance, member experience, operational efficiency, and competitive positioning balanced with risk management effectiveness and compliance.
โ€ข Collaborate with business and technology leaders to prioritize enterprise data initiatives and investments and ROI.
โ€ข Develop a data portfolio of business cases, cost-benefit analyses, and investment recommendations related to enterprise data, analytics, information management, and modernization initiatives.
โ€ข Partner with the PMO to oversee the enterprise data portfolio, resource planning, prioritization, and execution of data-related initiatives.
โ€ข Lead management reviews and opportunity assessments focused on process efficiency, cost optimization, business growth, and innovation opportunities.


Data Governance and Information Management
โ€ข Lead the Bank's enterprise data governance and information management programs.
โ€ข Establish and maintain enterprise data policies, standards, controls, procedures, communications, and governance frameworks.
โ€ข Define and oversee processes for monitoring compliance with enterprise data policies and standards.
โ€ข Establish and report key performance indicators (KPIs) and key risk indicators (KRIs) related to data governance, data quality, and information management effectiveness.
โ€ข Collaborate with Information Security, Compliance, Enterprise Risk Management, Legal, and Internal Audit to ensure adherence to regulatory, privacy, security, and risk management requirements.
โ€ข Promote enterprise-wide adoption of governance standards and confidence in enterprise data assets, reports, dashboards, data products, and analytical solutions.
โ€ข Oversee enterprise reference data, master data, metadata management, business glossary, data stewardship, and data lineage programs.
โ€ข Lead the Enterprise Data Quality Program, including data quality standards, monitoring processes, issue remediation procedures, and reporting.
โ€ข Ensure trusted and reliable data is available to support operational, analytical, regulatory, and strategic decision-making.
โ€ข Oversee service level agreements (SLA), data contracts, operational metrics, and performance targets related to enterprise data services.
โ€ข Oversee the lifecycle management of enterprise information assets from creation through retention, archival, and disposition.


Data Product Management
โ€ข Lead and manage the Bank's Data Product Owner function.
โ€ข Establish and mature a data product operating model aligned with business priorities.
โ€ข Define success metrics and accountability measures for enterprise data products.
โ€ข Ensure enterprise data products deliver measurable business value and support strategic initiatives.
โ€ข Report on the performance of data product contracts for consumers and applications.
โ€ข Partner with business leaders to prioritize data product investments and enhancements.
โ€ข Promote adoption and utilization of enterprise data products and a data marketplace across the organization along with establish trust metrics.
Artificial Intelligence and Data Enablement
โ€ข Partner with business and technology leaders to identify opportunities and use cases supporting artificial intelligence, advanced analytics, automation, and decision intelligence initiatives.
โ€ข Ensure enterprise data assets are governed, documented, trusted, and managed to support AI and machine learning use cases.
โ€ข Establish data quality, metadata, lineage, semantics, context, and governance standards required to support responsible AI initiatives.
โ€ข Collaborate with the Bank's AI governance framework and stakeholders to ensure AI solutions are supported by appropriate data controls and oversight for transparency and explainability.
โ€ข Assess enterprise data readiness for AI initiatives and identify required improvements.
โ€ข Develop strategies to improve data accessibility and trust by enhancing data quality, usability, and availability for AI and advanced analytics applications.
โ€ข Monitor emerging trends in AI, analytics, and data management and recommend opportunities that align with the Bank's strategic objectives.
Enterprise Data Architecture and Modernization
โ€ข Define, maintain, and communicate the Bank's enterprise data architecture strategy and roadmap.
โ€ข Collaborate with Infrastructure and Application Development teams to establish target state and optimal integration architectures for enterprise data platforms, analytical environments, information repositories, metadata management, and integration capabilities.
โ€ข Lead strategic planning for modernization of the Enterprise Data Warehouse, data integration capabilities, semantic layers, and supporting data platforms.
โ€ข Establish enterprise standards for data models, data products, metadata structures, integration patterns, data lineage, and information architecture.
โ€ข Collaborate with Infrastructure, Application Development, and business stakeholders to ensure alignment between business requirements, data architecture, and technology capabilities to ensure SLAs, business continuity, and disaster recovery scenarios.
โ€ข Guide evaluation and selection of data management, integration, analytics, and governance technologies.
โ€ข Ensure enterprise data architecture supports regulatory reporting, operational reporting, analytics, data products, AI initiatives, and future business requirements.
โ€ข Establish governance requirements at every level for future-state data platforms and integration capabilities.
โ€ข Review and approve governance, metadata, data quality, and business readiness aspects of major platform releases and modernization initiatives.
โ€ข Monitor emerging industry trends and recommend improvements to the Bank's enterprise data ecosystem.
Enterprise Content Management (ECM)
โ€ข Lead the Bank's Enterprise Content Management strategy, roadmap, governance framework, and operating model.
โ€ข Oversee lifecycle management of unstructured information assets and content repositories.
โ€ข Ensure ECM solutions support information governance, records management, regulatory compliance, operational efficiency, and digital transformation initiatives.
โ€ข Establish standards for enterprise information classification, retention, archival, and disposition.
โ€ข Collaborate with business and technology teams to improve document management, workflow automation, information accessibility, and adherence to information lifecycle regulations.
โ€ข Support modernization of ECM capabilities and integration with enterprise information management practices.
Leadership and Talent Development
โ€ข Lead, mentor, develop, and manage DSGO personnel
โ€ข Provide leadership for Data Governance, Data Product Management, Data Quality, ECM, and related information management functions.
โ€ข Build organizational capabilities in governance, architecture, information management, analytics, and AI readiness.
โ€ข Develop succession plans and talent strategies to support future organizational needs.
โ€ข Champion enterprise data culture and community building through data literacy, education programs, and meetup events.
โ€ข Promote a culture of accountability, collaboration, innovation, continuous improvement, and business partnership.


Minimum Qualifications


Experience
โ€ข 10+ years of progressive leadership experience in data management, data governance, data architecture, analytics, information management, or related disciplines.
โ€ข 5+ years leading enterprise-scale data governance and data strategy programs.
โ€ข Demonstrated experience leading enterprise data modernization initiatives.
โ€ข Experience with enterprise data architecture, data warehousing, and data integration platforms.
โ€ข Experience supporting artificial intelligence, machine learning, advanced analytics, or automation initiatives.
โ€ข Experience leading data quality, information governance, or enterprise content management programs.
โ€ข Experience working within a regulated financial services environment.
โ€ข Experience presenting recommendations and strategy to executive leadership and governance committees.
Knowledge and Skills
โ€ข Enterprise Data Governance
โ€ข Data Management and DAMA DMBOK
โ€ข Data Product Management
โ€ข Data Quality Management
โ€ข Metadata Management
โ€ข Master and Reference Data Management
โ€ข Information Lifecycle Management
โ€ข Enterprise Content Management
โ€ข AI Data Governance and Responsible AI Principles
โ€ข Business Intelligence and Analytics
โ€ข Regulatory and Risk Management Practices
โ€ข Strategic Planning and Organizational Leadership
โ€ข Demonstrated ability to lead enterprise data architecture and modernization initiatives.


Education
Bachelor's degree in Computer Science, Information Systems, Data Management, Business Administration, or a related field.
Master's degree preferred.

Work Environment:
Hybrid โ€“ Employees will work from both remote and onsite locations. Employees must live within a reasonable commuting distance of the office and are required to be onsite at least two (2) days per week, specifically on Tuesdays and Wednesdays. Certain positions or business needs may require additional in-office days.

General Notice:
This position description describes the general nature and level of work performed by the employee assigned to this position and should not be interpreted as all inclusive. It does not state or imply that these are the only duties and responsibilities assigned to the position. The employee may be required to perform other job-related duties. All requirements are subject to change and to possible modification to reasonably accommodate individuals with a disability.

This position description does not constitute an employment agreement between the Bank and employee and is subject to change by the employer as the needs of the Bank and requirements of the position change.

AA/EOE

QualificationsSkillsBehaviors

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Motivations

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EducationExperienceLicenses & Certifications

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.For further information, please review the Know Your Rights notice from the Department of Labor.

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