data quality manager

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Science Manager with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to lead a team ensuring the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. 
 
Key job responsibilities 
As part of the AGI team, an Applied Science Manager will lead and mentor a team of Applied Scientists who develop comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. The manager will guide the team in designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that align with core scientist team developing Amazon Nova models. The Applied Science Manager will oversee expert-level manual audits, meta-audits to evaluate auditor performance, and provide coaching to uplift overall quality capabilities across the team. The manager will lead research in areas related to HIL data impact to LLM models, and define utility measurement strategies for data generated by AGI-DS for Nova models.
 
 
The Applied Science Manager will be responsible for recruiting, hiring, and developing team members, conducting performance reviews, setting clear expectations and growth plans, and fostering a culture of scientific excellence and innovation. The manager will communicate with senior leadership, cross-functional technical teams, and customers to collect requirements, describe product features and technical designs, and articulate product strategy. 
 
A day in the life 
An Applied Science Manager with the AGI team will lead quality solution design, guide root cause analysis on data quality issues, drive research into new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. The manager will work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice. The manager will also conduct regular 1:1s with team members, provide mentorship and coaching, and ensure the team delivers high-impact results aligned with organizational goals.<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of scientists or machine learning engineers management experience</li><li>Knowledge of ML, NLP, Information Retrieval and Analytics</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience building machine learning models or developing algorithms for business application</li><li>Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, WA, BELLEVUE - 183,800.00 - 248,700.00 USD annually</div>

Applied Science Manager, Artificial General Intelligence , Quality Automation

<div>
 
 Job Description:
 
 
 
 
 
 
 Job Description:
 
 
 
 
 
 <ul>
 <li>
 Lead and support data governance initiatives, ensuring alignment with enterprise data strategy and regulatory compliance.
 </li>
 <li>
 Act as a trusted advisor to business and IT stakeholders, providing guidance on governance frameworks, policies, and best practices.
 </li>
 <li>
 Gather, analyze, and document business requirements for data governance, data cataloging, data quality, and metadata management programs.
 </li>
 <li>
 Collaborate with data stewards, data owners, and technical teams to define roles, responsibilities, and workflows for governance processes.
 </li>
 <li>
 Drive adoption and change management for governance tools and practices across business units.
 </li>
 <li>
 Support implementation and configuration of data governance platforms (e.g., Informatica Axon/EDC, Collibra, Alation).
 </li>
 <li>
 Define data quality rules, metrics, and dashboards; facilitate remediation of data issues.
 </li>
 <li>
 Develop and maintain governance artifacts such as data dictionaries, lineage documentation, and stewardship workflows.
 </li>
 <li>
 Conduct stakeholder workshops, training sessions, and awareness programs to promote governance maturity.
 </li>
 <li>
 Provide insights and recommendations for improving governance processes and operational efficiency.
 </li>
 <li>
 Track program KPIs, prepare status reports, and escalate risks to leadership as needed.
 </li>
 <li>
 Stay informed on industry trends, emerging technologies, and regulatory changes impacting data governance.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Skills Required
 
 
 
 
 
 <ul>
 <li>
 Strong understanding of Data Governance principles, frameworks, and regulatory compliance requirements.
 </li>
 <li>
 Knowledge of data quality concepts, profiling techniques, and remediation processes.
 </li>
 <li>
 Familiarity with data lineage, classification, and stewardship models.
 </li>
 <li>
 Excellent business analysis skills: requirements gathering, stakeholder engagement, and documentation.
 </li>
 <li>
 Ability to translate business needs into technical specifications for governance tools and workflows.
 </li>
 <li>
 Strong communication, facilitation, and presentation skills for cross-functional collaboration.
 </li>
 <li>
 Analytical mindset with problem-solving skills and attention to detail.
 </li>
 <li>
 Exposure to data architecture, data modeling, and enterprise data strategies.
 </li>
 <li>
 Conceptual understanding and hands-on experience of using data cataloging and metadata management tools (e.g., Informatica EDC/Axon, Collibra, Alation).
 </li>
 <li>
 Experience with reporting and visualization tools for tracking governance KPIs (e.g. Excel, Power BI, Tableau).
 </li>
 <li>
 Experience in consultative roles, providing strategic recommendations and influencing senior stakeholders.
 </li>
 <li>
 12-20 years of overall IT experience in Data &amp; Analytics with 8-10 years specifically working on multi-year/E2E/greenfield Data Management (Data Governance, Metadata Management &amp; Cataloging, Data Quality, Master/Reference Data Management) programs &amp; rollouts.
 </li>
 <li>
 Excellent verbal and written communication skill.
 </li>
 <li>
 Highly Desired secondary skill: Experience as a Scrum Master/Project Manager/Program Manager managing Data Governance projects/workstreams, with knowledge of Agile and hybrid delivery models, project planning, tracking &amp; reporting, risks issues dependencies management, stakeholder management.
 </li>
 <li>
 Highly Desired secondary skill: Experience of working with middle-east customers and regulations like NDMO, NDI, PDPL.
 </li>
 <li>
 Highly Desired secondary skill: Experience of Data Privacy regulations and project rollouts.
 </li>
 </ul>
 
 
</div>

Data Governance Consultant

Kemin

<div>Overview:
<div>
Kemin Industries is looking for a Data Governance Project Manager who can bring fresh perspective and new energy to a program with a strong foundation already in place. Two years into building our data governance framework, we&rsquo;re ready for someone who can elevate it even further - connecting AI, enterprise data, and governance into one cohesive, forward‑moving portfolio</div><div> 
You&rsquo;ll lead the governance workstream of a high‑priority AI initiative, partnering closely with IT, business units, and our AI consultant to strengthen data quality, define ownership, and turn complex requirements into practical processes. This role sits at the center of Kemin&rsquo;s data and AI evolution, perfect for someone who loves bringing clarity, structure, and momentum to a space that&rsquo;s growing fast and full of possibility.</div><div></div><div> 
This position will sit on-site at Kemin's WW Headquarters in Des Moines, Iowa.</div><div></div><div> 
Join the Kemin Team and Transform Lives!</div><div>
We are a privately held, family-owned-and-operated global biotechnology company driven by curiosity and committed to transforming the quality of life for people, pets, and the planet.</div><div></div><div> 
We create solutions that strengthen health and wellbeing, provide nutrition and immune support for pets and production animals, safeguard the planet&rsquo;s natural resources, and protect the global food supply chain for generations to come.</div><div></div><div> 
We supply over 500 specialty ingredients for various industries, including human and animal health and nutrition, pet food, aquaculture, nutraceutical, food technologies, crop technologies, textiles, biofuels, and animal vaccines.</div><div></div><div> 
We employ 3,500 global employees and operations in 90 countries, including manufacturing facilities in Belgium, Brazil, China, Egypt, India, Italy, San Marino, Singapore, South Africa, and the United States.</div><div>
As a valued member of our team, you'll enjoy a comprehensive benefits package designed to support your financial, physical, and professional well-being:</div><ul><li>
Competitive Financial Package: Enjoy a rewarding salary, uncapped bonus opportunities, a 401k match program, and generous paid vacation and holidays.</li><li>
Health and Wellness Support: Stay fit and healthy with our fitness reimbursement for the whole family, access to an on-site fitness center, a restaurant offering seasonal fresh food options, and free fresh fruit in break areas.</li><li>
Career Development and Advancement: Unlock your potential with opportunities for growth and development throughout your entire career.</li><li>
Continued Learning Opportunities: Grow your skills with our in-house learning platforms, offering thousands of training resources both live and online, and take advantage of tuition reimbursement for external post-secondary pursuits.</li><li>
Service Opportunities: Make a positive impact with paid time off for service, partnerships with The World Food Programme and Habitat for Humanity, and local community initiatives.</li></ul>
Responsibilities:
<ul><li>Execute organizational change management strategies to increase data literacy and adoption of data governance principles throughout a global workforce.</li><li>
Draft, implement, and maintain data policies, standards, and procedures; manage project documentation, version control, and governance templates.</li><li>
Develop and deliver comprehensive training programs on data governance policies, ensuring ongoing education and annual policy reviews.</li><li>
Identify and prioritize essential workflows, rigorously monitor project timelines, and drive continuous improvement in data quality.</li><li>
Track adherence to data governance policies, collaborate with data stewards to address non-compliance, and establish clear escalation mechanisms and engagement forums to maintain alignment and accountability.</li><li>
Coordinate the integration of data governance and AI initiatives across business units by managing cross-functional meetings, agendas, ethical AI practices, team onboarding, and regular project standups.</li><li>
Track data and AI project milestones, ROI, and success metrics; maintain risk registers, support A/B testing, and escalate blockers to leadership as needed.</li><li>
Enable effective two-way communication between technical and non-technical stakeholders by framing AI data risks, trade-offs, and decisions in accessible terms.</li><li>
Ensure the original intent of business, legal, and ethical decisions is preserved as they are operationalized in data and AI workflows, while aligning governance initiatives with evolving strategic priorities.</li><li>
Establish ongoing governance processes, including model review boards and knowledge transfer sessions between internal teams and external partners.</li></ul>
Qualifications:
<ul><li>Education<ul><li>
Bachelors Degree in Data Management, Computer Science, Information Systems, Business Administration, or related field. 5+ years of relevant experience</li></ul></li><li>
Strong leadership and stakeholder management abilities</li><li>
Understanding of how data governance supports business goals and strategy</li><li>
Skilled in developing training materials and conducting workshops</li></ul><div> 
Highly Preferred</div> 
<ul><li>
CSM (Scrum Master)</li><li>
Certifications in data governance (e.g., DAMA CDMP), data quality (e.g., IQ-DQ), PMP or MLOps</li><li>
Knowledge of data governance tools including Informatica, PowerBI, etc</li><li>
Understanding of metadata management, data lineage, and data quality frameworks</li><li>
Familiarity with A/B testing frameworks and their integration into analytical models</li><li>
Experience facilitating model validation and UAT sessions with diverse stakeholders</li><li>
Skilled in change management frameworks (e.g., Prosci, ADKAR) to support culture shifts</li><li>
Practical knowledge of AI governance concepts, including model lifecycle management, data lineage, quality controls, bias, fairness, explainability, and model risk management</li><li>
Experience in establishing, tracking, and reporting on AI performance and ROI metrics for executive audiences</li></ul><div> 
We are an equal opportunity employer. We consider all qualified applicants without regard to race, color, creed/religion, national origin, ancestry, citizenship or immigration status (where applicable), sex, sexual orientation, gender identity or expression, pregnancy/childbirth/breastfeeding or related conditions, age (40+), disability (including the use of a service animal), genetic information, marital status, familial or caregiver status, military or veteran status, status as a victim of domestic violence, reproductive health decision‑making, and any other status protected by applicable federal, state, or local law. We also prohibit retaliation for raising concerns or participating in an EEO process. Applicants who need a reasonable accommodation to apply or interview can email TalentAcquisition.US@Kemin.com.</div><div></div><div> 
A post-offer background check and drug screen is required. Additional pre-employment requirements may be necessary based on position.</div><div></div><div> 
Kemin is a drug-free and tobacco-free campus.</div><div></div><div> 
#LI-MP1</div></div>

Data Governance and AI Project Manager

Saher Management Consultancies LLC

<div>
 
 Saher Management is hiring for "Data Governance Administrator".
 
 
 
 
 Location:
 
 Doha, Qatar
 
 
 
 Overview
 
 
 
 Manage and oversee data governance activities, ensuring data quality, compliance, and effective governance policies across the organization. Drive standards, metadata management, and best practices to enable accurate, secure, and actionable data.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Lead data governance programs and initiatives.
 </li>
 <li>
 Define and enforce governance standards, policies, and business rules.
 </li>
 <li>
 Monitor compliance with governance rules and data standards.
 </li>
 <li>
 Act in multiple roles across data management cycles: power user, data custodian, steward.
 </li>
 <li>
 Analyze data anomalies and coordinate with stakeholders for data quality management.
 </li>
 <li>
 Support data classification, metadata management, and glossary development.
 </li>
 <li>
 Educate data users on proper data usage, protection, and governance practices.
 
 
 </li>
 </ul>
 
 Skills &amp; Competencies
 
 
 
 <ul>
 <li>
 Strong knowledge of relational databases and Big Data environments.
 </li>
 <li>
 Analytical thinking and problem-solving in data lifecycle management.
 </li>
 <li>
 Understanding of data protection, security, and compliance policies.
 </li>
 <li>
 Ability to standardize templates for reports, dashboards, and data insights.
 </li>
 <li>
 Effective stakeholder coordination and communication.
 
 
 </li>
 </ul>
 
 Qualifications &amp; Experience
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s in IT, Computer Science, Business Administration, or related field.
 </li>
 <li>
 10+ years in MDM applications, metadata management, data architecture, data quality, and data lineage.
 
 
 </li>
 </ul>
 
 Tools &amp; Tech
 
 
 
 <ul>
 <li>
 Microsoft Azure ecosystem
 </li>
 <li>
 Data management and metadata tools
 
 
 </li>
 </ul>
 
 Soft Skills
 
 
 
 <ul>
 <li>
 People management and leadership
 </li>
 <li>
 Achieving results &amp; professional orientation
 </li>
 <li>
 Business thinking &amp; strategic mindset
 
 
 </li>
 </ul>
 #DataGovernance #DataManagement #MDM #MetadataManagement #DataQuality #DataSecurity #DataArchitecture #Analytics #DohaJobs #ITGovernance
 
 
 Skills: metadata management,management,data governance,data management
</div>

Data Governance Administrator

Mashreq

<div>
 
 Job Purpose
 
 
 
 
 
 
 
 
 
 
 <ol>
 <li>
 
 Data Quality Strategy &amp; Governance
 
 </li>
 </ol>
 
 &bull; Define and implement data quality policies, standards, and procedures aligned with the bank&rsquo;s data governance framework.
 
 
 &bull; Collaborate with business and technology teams to define critical data elements (CDEs) and establish data quality rules.
 
 
 &bull; Drive data quality improvement initiatives across retail, corporate, international, treasury business areas and support and control functions.
 
 
 &bull; Ensure compliance with regulatory requirements and industry best practices for data quality.
 
 
 
 2. Data Quality Monitoring &amp; Issue Management
 
 
 
 &bull; Design and implement data quality measurement frameworks, including key data quality metrics (accuracy, completeness, timeliness, consistency, and validity).
 
 
 &bull; Lead the development of data quality dashboards and reports to track data quality trends and issues.
 
 
 &bull; Identify, assess, and remediate data quality issues through root cause analysis and corrective action plans.
 
 
 &bull; Work with technology teams to implement automated data quality controls and monitoring solutions.
 
 
 
 
 
 3.
 
 Stakeholder Engagement &amp; Collaboration
 
 
 
 &bull; Act as a subject matter expert (SME) for data quality across business functions, risk, finance, compliance, and technology teams.
 
 
 &bull; Partner with data stewards, data owners, and data engineers to enforce data quality standards.
 
 
 &bull; Support business teams in embedding data quality requirements into operational processes.
 
 
 &bull; Conduct training and awareness sessions on data quality best practices.
 
 
 
 
 
 4.
 
 Technology &amp; Automation
 
 
 
 &bull; Collaborate with technology teams to integrate data quality tools into the bank&rsquo;s data architecture.
 
 
 &bull; Leverage AI/ML-driven data quality solutions to enhance data profiling and anomaly detection.
 
 
 &bull; Evaluate and recommend new data quality tools and technologies.
 
 
 
 
 
 Key result Areas
 
 
 
 
 <ol>
 <li>
 
 Data Quality Strategy &amp; Governance
 
 </li>
 </ol>
 
 &bull; Define and implement data quality policies, standards, and procedures aligned with the bank&rsquo;s data governance framework.
 
 
 &bull; Collaborate with business and technology teams to define critical data elements (CDEs) and establish data quality rules.
 
 
 &bull; Drive data quality improvement initiatives across retail, corporate, international, treasury business areas and support and control functions.
 
 
 &bull; Ensure compliance with regulatory requirements and industry best practices for data quality.
 
 
 
 2. Data Quality Monitoring &amp; Issue Management
 
 
 
 &bull; Design and implement data quality measurement frameworks, including key data quality metrics (accuracy, completeness, timeliness, consistency, and validity).
 
 
 &bull; Lead the development of data quality dashboards and reports to track data quality trends and issues.
 
 
 &bull; Identify, assess, and remediate data quality issues through root cause analysis and corrective action plans.
 
 
 &bull; Work with technology teams to implement automated data quality controls and monitoring solutions.
 
 
 
 
 
 3.
 
 Stakeholder Engagement &amp; Collaboration
 
 
 
 &bull; Act as a subject matter expert (SME) for data quality across business functions, risk, finance, compliance, and technology teams.
 
 
 &bull; Partner with data stewards, data owners, and data engineers to enforce data quality standards.
 
 
 &bull; Support business teams in embedding data quality requirements into operational processes.
 
 
 &bull; Conduct training and awareness sessions on data quality best practices.
 
 
 
 
 
 4.
 
 Technology &amp; Automation
 
 
 
 &bull; Collaborate with technology teams to integrate data quality tools into the bank&rsquo;s data architecture.
 
 
 &bull; Leverage AI/ML-driven data quality solutions to enhance data profiling and anomaly detection.
 
 
 &bull; Evaluate and recommend new data quality tools and technologies.
 
 
 
 
 
 Knowledge, Skills and Experience
 
 
 
 
 
 The ideal candidate will demonstrate deep knowledge and a proven track record in the following areas:
 
 <ul>
 <li>
 Extensive experience in data-related projects or programs, with strong expertise in metadata management and data governance implementation.
 </li>
 <li>
 Practical experience in implementing data management standards (e.g., DAMA) within a banking environment.
 </li>
 <li>
 Strong understanding of data governance policies, standards, metrics, controls, and processes.
 </li>
 <li>
 Knowledge of legal, compliance, and regulatory issues impacting data, including geographic restrictions on data storage and data centers.
 </li>
 <li>
 Experience in identifying data assets, defining data ownership, and establishing usage and access control policies.
 </li>
 <li>
 Proficiency in data domain discovery, data classification, taxonomy, and hierarchies that support data catalog architecture.
 </li>
 <li>
 Ability to create or enhance business glossaries by working with business analysts and stakeholders to define clear, business-relevant terms.
 </li>
 <li>
 In-depth understanding of designing and developing data catalogs (e.g., Microsoft Purview) to inventory data assets and enable data discovery through unified search.
 </li>
 <li>
 Experience in integrating and maintaining data dictionaries, business glossaries, and data catalogs.
 </li>
 <li>
 Ability to facilitate metadata capture as part of change and operational deliverables.
 </li>
 <li>
 Hands-on experience with Informatica Data Governance tools (e.g., EDC, Axon, DEQ), including planning and managing tool implementation projects.
 </li>
 <li>
 Experience in running data governance committees and effectively communicating the value and impact of data governance to business stakeholders through demos and presentations.
 </li>
 </ul>
 
 
</div>

Assistant Vice President - Data Governance (Mashreq Global Network Pakistan)

DP World

<div>Job Purpose:
To establish, maintain, and continuously improve the integrity, quality, and governance of master data across the global freight forwarding organization. This role serves as the central authority for Master Data Management processes, tools, and standards, ensuring accurate, consistent, and accessible data that enables operational excellence, regulatory compliance, and strategic decision-making across all regions and business functions.
Key Accountabilities:
MDM Governance &amp; Strategy
Framework Development: Design, implement, and maintain a comprehensive MDM governance framework that defines data ownership, accountability, policies, standards, and procedures across the freight forwarding operations
Policy Management: Establish and enforce global MDM policies, data quality standards, and data stewardship principles to ensure consistency across all regions
Stakeholder Governance: Lead MDM data stewardship council and working groups with cross-functional stakeholders including Operations, IT, Commercial, Finance, and Compliance teams
Compliance Oversight: Ensure MDM practices align with regulatory requirements including data privacy regulations (GDPR, etc.), customs regulations, and industry standards
Change Management: Drive adoption of MDM processes through effective change management, communication strategies, and stakeholder engagement
Process Design &amp; Implementation
Process Documentation: Define and document standardised global MDM processes for data creation, validation, maintenance, deactivation, and archival across all master data domains (customers, vendors, products, locations, tariffs, etc.)
Workflow Design: Design and implement efficient workflows for data requests, approvals, and updates that balance data quality with operational speed
Best Practices: Establish MDM best practices and standard operating procedures (SOPs) aligned with industry standards and organizational objectives
Process Optimization: Continuously review and optimize MDM processes to improve efficiency, reduce errors, and enhance user experience
Integration Management: Coordinate MDM processes with upstream and downstream systems to ensure seamless data flow across the technology ecosystem
Data Quality Management
Quality Framework: Develop and implement data quality frameworks including quality metrics, KPIs, and monitoring dashboards
Quality Routines: Establish regular data quality routines including data profiling, cleansing, validation, enrichment, and reconciliation activities
Issue Resolution: Identify, investigate, and resolve data quality issues; implement corrective and preventive actions
Data Standards: Define and maintain data standards, naming conventions, taxonomies, and reference data across all master data domains
Monitoring &amp; Reporting: Create and maintain data quality scorecards and reports for management, highlighting trends, issues, and improvement opportunities
Technology &amp; Automation
Tool Management: Oversee the implementation, configuration, and optimization of MDM tools and platforms used across the organization
Third-Party Collaboration: Partner with external vendors and technology providers to enhance MDM capabilities, integrate new data sources, and implement automation solutions
Automation Initiatives: Identify and drive automation opportunities to reduce manual data entry, improve data accuracy, and accelerate data processing
System Integration: Work with IT teams to ensure MDM systems integrate effectively with operational systems (CR3, CRM, NPM, Customer Platform, Quote Tool, Oracle Fusion, etc.)
Innovation: Stay current with emerging MDM technologies, AI/ML capabilities for data management, and industry innovations; recommend and implement relevant solutions
Training &amp; Support
Training Programs: Develop and deliver MDM training programs for data stewards, regional teams, and end users to build data management capabilities
User Support: Provide guidance and support to regional and functional teams on MDM processes, tools, and data quality issues
Documentation: Create and maintain comprehensive user guides, training materials, and knowledge repositories for MDM processes and systems
Community Building: Foster a community of data stewards and champions across regions to promote data quality culture and share best practices
Regional &amp; Cross-Functional Collaboration
Regional Coordination: Work closely with regional operations teams to understand local requirements while maintaining global standards
Cross-Functional Alignment: Collaborate with Commercial, Finance, Operations, and other business functions to ensure MDM supports business objectives
IT Partnership: Partner with Global IT teams on system implementations, upgrades, and integrations affecting master data
Business Analysis: Gather and analyze business requirements for MDM enhancements from various stakeholders globally
Performance &amp; Continuous Improvement
Metrics &amp; KPIs: Define, track, and report on MDM performance metrics including data quality scores, process efficiency, user satisfaction, and business impact
Audit &amp; Assessment: Conduct regular audits of master data quality, process compliance, and system usage across regions
Improvement Initiatives: Lead continuous improvement projects to enhance data quality, streamline processes, and increase automation
Benchmarking: Monitor industry best practices and benchmark organizational MDM maturity against industry standards
Collaboration
Cross-Functional Collaboration: Work with global, regional, and cross-functional teams to ensure consistent processes and standards.
Stakeholder Engagement: Engage with stakeholders to gather input and feedback for system and training enhancements.
Qualifications, Skills and Experience:
Required
Bachelor's degree in Information Systems, Data Management, Business Administration, Supply Chain Management, or related field
Minimum 5-7 years of experience in Master Data Management, Data Governance, or Data Quality Management
Experience in freight forwarding, logistics, or supply chain operations
Proven track record of implementing and managing MDM processes and tools at enterprise scale
Strong understanding of data governance frameworks and data quality methodologies
Experience working with MDM platforms and data management technologies
Knowledge of freight forwarding operations, terminology, and data structures (customers, shipments, tariffs, locations, etc.)
Demonstrated project management skills with ability to lead cross-functional initiatives
Experience collaborating with third-party vendors and technology providers
Preferred
Master's degree in relevant field
Professional certifications in Data Management (CDMP, DGSP) or related areas
Experience with specific MDM tools (e.g., Informatica, Semarchy, Microsoft MDS, Profisee)
Knowledge of data privacy regulations (GDPR, CCPA) and compliance requirements
Experience with data analytics, visualization tools, and reporting platforms
Familiarity with Agile/Scrum methodologies
International or multi-regional experience in global organizations</div>

Global Manager - MDM Systems & Process

National Bank of Bahrain

<div>
 
 
 Job Purpose
 
 
 
 
 
 
 The role holder is responsible for establishing and institutionalizing the Bank&rsquo;s enterprise data governance framework, ensuring clear data ownership, stewardship, accountability, and control across all critical systems and data domains. The role holder will define and formalize data ownership structures across business and technology platforms, ensuring that every critical data element has a clearly assigned owner and steward. The role is accountable for governing the creation and use of data reports including departmental reports to ensure alignment with the approved &ldquo;single source of truth&rdquo; and prevent fragmented or uncontrolled data usage. This role operates at driving cross-functional alignment, enforcing governance standards, and ensuring that data assets are accurate, controlled, reconciled, and fit for business, financial, and regulatory reporting purposes.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 
 
 Data Ownership &amp; Accountability Framework
 
 
 <ul>
 <li>
 Establish and maintain a formal Data Ownership and Data Stewardship framework across all key banking systems and data domains.
 </li>
 <li>
 Define and document accountability for Critical Data Elements (CDEs), ensuring business owners formally accept responsibility for data accuracy and integrity.
 </li>
 <li>
 Ensure ownership structures are embedded within operational processes and governance forums.
 </li>
 <li>
 Escalate unresolved data ownership gaps to relevant governance committees.
 </li>
 </ul>
 
 
 
 
 
 Data Governance &amp; Compliance
 
 
 <ul>
 <li>
 Support and coordinate the implementation of the bank&rsquo;s Data Governance framework, guiding teams to consistently apply governance policies across relevant data domains.
 </li>
 <li>
 Support regulatory readiness by ensuring data used for reporting aligns with supervisory guidelines.
 </li>
 <li>
 Collaborate with different stakeholders to capture and refine data requirements linked to reporting, analytics, and regulatory needs.
 </li>
 <li>
 Facilitate workshops to formalize data definitions, data usage boundaries, and Critical Data Element prioritization, ensuring alignment across departments.
 </li>
 <li>
 Provide structured analysis bridging business requirements and technical data structures, enabling accurate and consistent data consumption across systems.
 </li>
 </ul>
 
 
 
 
 
 Data Modeling &amp; Architecture
 
 
 <ul>
 <li>
 Oversee the development and maintenance of conceptual, logical, and physical data models across assigned banking domains (e.g., retail, corporate, risk, finance, treasury).
 </li>
 <li>
 Ensure models adhere to established enterprise data standards, naming conventions, and modeling methodologies.
 </li>
 <li>
 Ensure data models support large-scale, high-accuracy financial calculations and reconciliations that align with regulatory, statutory, and internal reporting requirements.
 </li>
 </ul>
 
 
 
 
 
 Data Quality, Controls &amp; Assurance
 
 
 <ul>
 <li>
 Define and operationalize Data Quality control frameworks, including profiling, validation rules, exception workflows, and remediation cycles.
 </li>
 <li>
 Lead cross‑functional efforts to resolve data issues, including root‑cause analysis, corrective actions, and long‑term data‑quality improvements.
 </li>
 <li>
 Maintain oversight of reconciliation processes across financial, operational, and regulatory data pipelines to ensure consistent, trusted data outputs. Support Model Implementation &amp; Delivery.
 </li>
 <li>
 Partner with data engineering to ensure models are correctly implemented in databases and reporting systems.
 </li>
 <li>
 Participate in system testing, UAT, and validation of data migrations and new product implementations.
 </li>
 </ul>
 
 
 
 
 
 Qualifications &amp; Experience
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in in Finance, Data Analytics, Computer Science, Information Systems, or in any other subject or equivalent is required.
 </li>
 <li>
 Master&rsquo;s degree in Finance, Data Analytics, Computer Science, Information Systems, or a related field is preferred.
 </li>
 <li>
 Professional qualification in related subjects to Data Analytics, Computer Science, Data Governance is preferred.
 </li>
 <li>
 Minimum 3-4 years of practical experience in a bank or same or similar function.
 </li>
 </ul>
 
 
</div>

Data Governance Lead

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