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Concord IT Systems

Data Solution Architect

Austin, TX · On-site

$140K/yr

... DCAM • Expertise in Data Architecture (having sound understanding of various Data Models and Warehouse Architecture) • Experience in Reporting and Visualization, Tableau, ETL (Tools like IICS ...

TechNix LLC

Data Engineer

Montgomery, AL · On-site

$113.30K - $136K/yr

Knowledge of DAMA-DMBoK, DCAM, MDM concepts, and governance frameworks. (8-10 Years) * Experience with Microsoft Purview, Fabric, MS Power BI, and Key Vault (5-8 Years) * Familiarity with AI/ML data ...

Advanced Systems Design

Data Quality Engineer

Montgomery, AL

$113.20K - $136K/yr

Knowledge of DAMA-DMBoK, DCAM, MDM concepts, and governance frameworks. (8-10 Years) * Experience with Microsoft Purview, Fabric, MS Power BI, and Key Vault (5-8 Years) * Familiarity with AI/ML data ...

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As of Jun 4, 2026, the average hourly pay for dcam in the United States is $67.44, according to ZipRecruiter salary data. Most workers in this role earn between $65.38 and $71.15 per hour, depending on experience, location, and employer.

What is a DCAM job?

A DCAM (Data Capability Assessment Model) job typically involves evaluating and improving an organization's data management capabilities. Professionals in this role assess data governance, quality, architecture, and operations to ensure efficient data-driven decision-making. They often work with frameworks like the DCAM model to benchmark and enhance data management practices. This role is crucial for organizations looking to optimize data strategy and compliance.

What are the key skills and qualifications needed to thrive in the Dcam position, and why are they important?

To thrive as a DCAM (Data Capability Assessment Model) specialist, you need a strong background in data management, data governance, and business analysis, ideally supported by relevant certifications such as DCAM accreditation or experience with industry frameworks. Familiarity with tools such as data cataloging platforms, data quality assessment software, and data lineage systems is often required. Excellent communication, stakeholder management, and analytical problem-solving skills help in driving organizational change and translating business needs into data solutions. These capabilities ensure effective assessment and improvement of an organization's data management maturity, supporting strategic decision-making and regulatory compliance.

What are some common challenges faced by DCAM specialists during data capability assessments?

DCAM specialists often encounter challenges in aligning diverse business units on data management standards and effectively communicating the value of mature data practices to non-technical stakeholders. Navigating varying levels of data literacy across teams, handling resistance to process changes, and ensuring data governance initiatives are adopted organization-wide are typical hurdles. Additionally, balancing thorough assessment with tight project timelines can require strong project management skills. Successfully overcoming these challenges involves both technical knowledge and the ability to foster collaboration and consensus.
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Infographic showing various Dcam job openings in the United States as of May 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 82% In-person, 9% Hybrid, and 9% Remote job distribution, with an average salary of $140,265 per year, or $67.4 per hour.

Data and AI Governance Manager

U.S. Financial Technology

Remote

Full-time

Medical, Retirement, PTO

Posted 9 days ago

Job description

OVERVIEW
The Company
U.S. Financial Technology (U.S. FinTech) is seeking an experienced Data and AI Governance Manager to join our team of talented professionals. This is a full-time remote opportunity.
U.S. FinTech built and operates the largest and most advanced mortgage securitization platform in the world, supporting the Uniform Mortgage-Backed Security (UMBS) of Fannie Mae and Freddie Mac.
Supporting 70% of the mortgage-backed securities in the market, U.S. FinTech provides best-in-class single-family issuance, bond administration, disclosure, and tax services. We support a broad portfolio of products for our clients with full lifecycle management.
Our market-leading, cloud-based, end-to-end platform executes transactions on an extraordinary scale which has bolstered liquidity in the secondary mortgage market, one of the largest and most important financial markets in the world. Our unique approach to securitization combines the best minds in financial services with the know-how, flexibility, and innovation of leading technologists.
RESPONSIBILITIES
Job Information
The Data and AI Governance Manager is a leadership role responsible for designing, embedding, and continuously maturing the enterprise-wide framework that governs how data and AI are sourced, managed, protected and deployed across the organization.
Operating at the intersection of data strategy, AI risk, and regulatory compliance within a highly regulated financial services environment, the role ensures the organization's practices align with industry standards including DCAM, NIST AI RMF and ISO 42001, while proactively managing emerging AI and data risks.
The manager works in close relationships with Data & AI engineering, Risk & Compliance, Legal and Business Units to translate policies into operational practices and embed a culture of responsible data and AI use. Reporting directly to the VP, Data and AI, this role plays a pivotal part in shaping the organization's governance posture as it scales its AI capabilities and navigates on evolving regulatory landscape.
Key Job Functions
  • Strategy & Framework Design
    • Lead the design, implementation, and continuous improvement of the enterprise Data & AI Governance framework, aligned to DCAM maturity levels, NIST AI RMF core functions, and ISO 42001 requirements.
    • Own & Direct the development and lifecycle management of data governance policies, AI governance standards, data quality rules, and metadata management practices across all business domains.
    • Partner in driving the organization's AI governance roadmap, ensuring AI systems are inventoried, risk-classified, and governed through structured review and approval processes prior to deployment.
    • Define and maintain a clear governance operating model, including data stewardship accountabilities, decision rights, escalation paths, and governance council structures.
    • Explore and integrate emerging technologies, including AI, to streamline governance workflows, improve metadata curation and strengthen quality and compliance monitoring.

    Risk, Compliance & Regulatory Alignment
    • Ensure ongoing alignment with FHFA and other relevant regulations and emerging AI-specific regulatory requirements across all jurisdictions of operation.
    • Partner with Risk, Compliance, Legal, and Internal Audit teams to identify data and AI-related risks, define controls, and ensure gaps are tracked and remediated in a timely manner.
    • Monitor the organization's DCAM assessment scores and NIST AI RMF profile, conducting periodic gap analyses and preparing executive-level maturity reports for the VP, Data & AI and senior stakeholders.
    • Champion responsible and ethical AI practices, including fairness, explainability, transparency, and accountability requirements in alignment with ISO 42001 and internal AI ethics principles.

    Data Quality & Stewardship
    • Establish and embed enterprise data quality standards and measurement frameworks, working with Data Stewards across business domains to drive accountability and remediation.
    • Oversee data classification, critical data element identification, metadata management, and Collibra DIC management to ensure consistent governance across all data domains.
    • Facilitate the Data Governance Council and domain stewardship forums, preparing agenda, tracking actions, and ensuring governance decisions are documented and communicated effectively.

    Stakeholder Engagement & Culture
    • Collaborate with senior leaders across Business, Finance, Risk, Technology, and Legal & Compliance to gain buy-in, embed governance accountabilities, and resolve cross-functional data and AI governance issues.
    • Advocate for a data-literate and AI-responsible culture by developing awareness programs, training curricula, and communication strategies that build governance knowledge across the organization.
    • Influence product and technology decisions by providing governance counsel during the design and procurement of data systems, AI platforms, and third-party AI tools.

    Team Leadership & Development
    • Manage & Develop a high-performing team of five governance professionals, setting clear objectives, providing coaching, conducting performance reviews, and fostering an inclusive and collaborative team culture.
    • Allocate team capacity and resources effectively across governance tasks and initiatives, ensuring delivery against agreed milestones and outcomes.
    • Mentor team members on data governance methodologies, AI risk concepts, and industry frameworks to build internal capability and career growth.
    • Develop and manage the annual budget for the data governance team, optimizing investment across tools - for example metrics dashboard, AWS expenses, training etc.

    Reporting & Performance Metrics
    • Define and maintain a suite of governance KPIs and KRIs (e.g., data quality scores, AI risk incident rates, policy compliance rates, stewardship coverage) reported to the VP, Data & AI on a regular basis.

QUALIFICATIONS
Education
  • Bachelor's degree or equivalent required

Minimum Experience
  • Minimum 8 years of progressive experience in data governance, data management, AI governance, or risk & compliance roles, with at least 3 years in a leadership or management capacity.
  • Minimum 3 years of direct people management experience.
  • Minimum of 1 year of experience designing and implementing enterprise-wide AI governance frameworks.
  • Applicants must be authorized to work in the US without requiring employer sponsorship currently or in the future. U.S. FinTech does not offer sponsorship for this position.

Specialized Knowledge & Skills
  • Demonstrated experience designing and implementing enterprise-wide data governance frameworks using DCAM, NIST AI RMF, ISO 42001, or equivalent standards.
  • Proven track record of managing governance programs in a regulated financial services environment.
  • Experience leading cross-functional governance initiatives and operating governance bodies such as Data Councils, AI Review Boards, or Stewardship Forums.
  • Hands-on experience with data governance tooling (e.g., Collibra, Alation, Microsoft Purview, or similar) and familiarity with AI/ML lifecycle management platforms.
  • Strong people management skills with a demonstrated ability to build, lead, and retain high-performing teams in a matrix organization.
  • Excellent stakeholder management and communication skills, with the ability to influence senior executives and translate governance concepts into business value.

Pay Range $181,000 to $205,500
U.S. FinTech's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) a candidate's qualifications, skills, competencies, and experience, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law. U.S. FinTech offers a competitive total compensation package, which includes a performance bonus, 401k match, healthcare coverage, PTO, and a broad range of other benefits.
Employment
As a condition of employment with U.S. Financial Technology, any successful job applicant will be required to successfully complete a background investigation, which may also include a credit check for positions in some areas of our business.
U.S. Financial Technology is an Equal Opportunity Employer.
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