189 Data Managers jobs in the United Arab Emirates

The organization seeks a seasoned professional to spearhead the establishment and upkeep of a Data Governance program focused on data quality. This pivotal role necessitates a candidate with exceptional leadership skills, as they will be responsible for steering the development, implementation, and ongoing evaluation of data management strategies.

The job holder is responsible for leading the design, development, and implementation of the Data Governance program, specifically those relating to data quality as part of the Data Governance Office. They are accountable for maintaining direction and ensuring alignment with business objectives regarding how data is managed across the organization.

The job holder is also a key member of the broader data management group across the organization and is expected to play an important role in influencing and providing direction to the wider data management community.

• Lead the development of the organizational Data Strategy as well as data management in line with strategic business objectives and FAB cultures and values.
• Manage and support the AVP data governance and data quality in the development and oversight of data governance framework standards, practices, policies, and processes.
• Lead the development of the Data Governance Office as a center of excellence committed to ingraining a data-driven decision-making culture across the organization, teaming with external partners and offering end-to-end data services across business and support groups.
• Lead and provide direction in the monitoring and analysis of the latest strategic technological and regulatory trends within the organization and on a global scale.
• Promote good data quality practices and the management of data as a strategic asset.

• Lead the production of information on performance and quality standards for data within the organization.
• Gather and create inputs for the management and reporting of data SLA and KPIs, including monitoring of data quality dashboards and SLA breaches, ensuring adherence to agreed SLA targets and demonstrating improvement against agreed targets.
• Lead and provide guidance and all necessary support to the AVP data governance and data quality in managing and resolving data quality issues, providing advice and guidance to all business areas.
• Advise on targets and monitoring standards with stakeholders for data entry and data collection undertaken.
• Responsible for leading/directing the development of DQ measurement/reporting/control capabilities.
• Responsible for leading/directing the development and maintenance of data quality rules.
• Responsible for leading/directing the development and maintenance of DQ profiling tools/methodologies.
• Responsible for leading the development and ongoing maintenance of data definitions, standards, lineage, and other data quality artifacts as part of the data catalog.
• Lead the development, maintenance, and management of organizational reference data.
• Provide subject matter expertise on systems/process developments to control and improve data quality.
• Lead the development of Data Quality Monitoring tools and DQ Dashboards and provide direction to subordinates.
• Support and guide the RCA team with analyzing data across applications from a Data Quality standpoint.
• Guide and provide necessary support to different Business units from a DQ point of view.

Internal:

• The role requires establishing strong working relationships with all business groups and support functions of the organization at various levels to ensure continued buy-in for the Data Governance Model.

External:

• The role requires regular interactions with vendors, data partners, consulting partners, and regulatory and governmental bodies.

• Delivery against planned DQ roadmap activities.
• # Outstanding high criticality data issues.
• Increase in stakeholder opinion of DQ.
• Improvement in DQ for key data elements.
• Feedback from peers, management, and key stakeholders.
• Demonstrate leadership and guide/monitor subordinates on technical activities and deliveries.

Qualifications:

• Degree educated with a minimum of 3 to 4 years of direct experience; 5 years overall industry experience.

• Minimum 3 to 4 years of direct experience in data-related programs, ideally in financial services.
• Experience of contributing to regulatory projects would be beneficial.
• Strong Data Governance skills; direct experience of developing Data Governance frameworks and/or performing a Data Governance Management role.
• Good operational knowledge of data quality management processes.
• Experience of collating, designing, and presenting top quality management information to senior leadership stakeholders.
• Excellent track record of delivering on strategic data initiatives.

• Good knowledge of Data Governance and Data Quality programs, frameworks, policies, and procedures.
• Experience working on strategic programs and synthesizing business requirements and priorities with existing organizational capabilities.
• Good knowledge of common DQ and dashboard tooling.
• Technical knowledge of common DQ tools and standards such as Informatica EDQ and Oracle EDQ.
• Good SQL knowledge.

• A reliable and trustworthy person able to anticipate and deal with the varying needs and concerns of numerous stakeholders, adapting personal style accordingly.
• Adaptable and knowledgeable, able to discuss a variety of data management situations with both IT and business stakeholders.

Remote Work:

No

Employment Type:

Full-time

We are seeking a highly skilled Data Quality Professional to join our team.

The ideal candidate will have a strong background in data governance and quality management, with experience leading data-related programs in financial services. They will be responsible for designing, developing, and implementing data governance frameworks and performing data governance management roles.

This role involves monitoring and analyzing the latest strategic technological and regulatory trends within the organization and on a global scale. The successful candidate will also provide guidance and support to subordinate staff members and demonstrate leadership skills.

The key responsibilities of this role include:

• Developing information on performance and quality standards for data within the organization.
• Collating, designing, and presenting top-quality management information to senior leadership stakeholders.
• Liaising with vendors, data partners, consulting partners, and regulatory bodies.
• Maintaining organizational reference data and ensuring its accuracy.
• Providing subject matter expertise on systems/process developments to control and improve data quality.

In addition to these responsibilities, the successful candidate will have excellent communication and interpersonal skills, as they will need to establish strong working relationships with various business groups and support functions at different levels within the organization.

The ideal candidate will possess the following qualifications:

• A degree in a relevant field (e.g., computer science, information technology, or mathematics).
• A minimum of 3-4 years of direct experience in data-related programs, ideally in financial services.
• Strong data governance skills, including experience developing data governance frameworks and/or performing data governance management roles.
• Good operational knowledge of data quality management processes.
• Excellent track record of delivering on strategic data initiatives.

The salary for this role is competitive and negotiable, depending on experience. Benefits include:

• A comprehensive health insurance plan.
• A retirement savings plan with employer matching.
• Tax-free benefits (where applicable).

We offer a dynamic work environment that fosters innovation and collaboration among employees. If you are passionate about data quality and governance and are looking for a challenging role that offers opportunities for growth and development, please apply today.

Data Quality Analyst role at Capgemini. Senior Data Quality Analyst – Capgemini.

About Capgemini: Capgemini is a global leader in consulting, digital transformation, technology, and engineering services with a presence in over 50 countries. Our collaborative, people-centric culture partners with clients across industries.

We are seeking a highly skilled Senior Data Quality Analyst with a robust background in designing, implementing, and maintaining data quality frameworks leveraging Python or Collibra. The ideal candidate will ensure data accuracy, consistency, completeness, and reliability across large-scale cloud-based platforms, especially within Azure Databricks environments. This role requires expertise in automated data quality assurance, a deep understanding of data governance, and hands-on experience integrating quality controls into modern data pipelines.

The Senior Data Quality Analyst will be embedded within an agile squad dedicated to a specific business mission while contributing to a broader program comprising 4 to 8 interconnected squads. Collaboration, technical leadership, and a continuous improvement mindset are essential as you work cross-functionally to elevate the organization's data quality standards.

1. Development & Integration
   • Design, develop, and implement automated data quality checks using Python scripts and libraries or Collibra Data Quality components.
   • Integrate data quality validation logic within existing ETL/ELT pipelines operating on Azure Databricks, ensuring quality gates are consistently enforced across all data flows.
   • Develop and maintain reusable Python modules that perform anomaly detection, schema validation, and rule-based data quality checks to enable rapid scaling of quality coverage.
   • Collaborate with data engineering teams to embed continuous quality controls throughout the data ingestion, transformation, and consumption lifecycle.
   • Support the deployment and management of Collibra-based data quality solutions to automate governance workflows and stewardship activities.
2. Data Quality Management
   • Define, measure, and rigorously enforce data quality metrics, thresholds, and Service Level Agreements (SLAs) tailored to business-critical datasets.
   • Utilize Collibra to manage and operationalize data governance workflows, maintain business glossaries, and delineate stewardship responsibilities.
   • Monitor the integrity of data pipelines for completeness, accuracy, timeliness, and consistency across distributed and cloud-native environments.
   • Conduct detailed root cause analyses for complex data quality issues, collaborating with engineers and domain experts to drive permanent remediation and prevention strategies.
   • Implement and continuously refine monitoring frameworks, utilizing dashboards and alerting systems (built using Python and Collibra integrations) for real-time visibility into key data quality indicators.
3. Support & Operations
   • Act as a Level 2/3 escalation point for data quality incidents, troubleshooting issues and coordinating with other agile squads and technical teams for rapid resolution.
   • Work closely with product owners, business analysts, and key stakeholders to understand evolving data requirements and ensure quality expectations are aligned and met.
   • Maintain and optimize operational dashboards for ongoing data quality monitoring, leveraging both Python-based and Collibra-integrated solutions.
   • Participate actively in agile ceremonies, including sprint planning, daily standups, reviews, and retrospectives, contributing to squad goals and continuous delivery improvements.
4. Governance & Best Practices
   • Establish, document, and evangelize data quality standards, validation frameworks, and best practices across squads and the broader data organization.
   • Maintain comprehensive documentation on validation rules, automated test cases, and quality assurance procedures, ensuring transparency and repeatability.
   • Mentor, coach, and upskill junior data engineers and analysts in data quality concepts, tools, and processes to foster a quality-first culture.
   • Ensure strict compliance with data governance, privacy, and security policies by leveraging Collibra's governance and stewardship frameworks.
   • Continuously assess emerging technologies, tools, and methodologies for potential enhancement of the data quality ecosystem.

• Bachelor's or Master's degree in Computer Science, Data Management, Information Systems, or a closely related field.
• Progressive experience in data quality engineering, data management, or related data roles within complex technology environments.
• Demonstrable expertise in Python, including the development of reusable data quality and validation libraries.
• Extensive hands-on experience with Azure Databricks, including cloud-native data processing, ETL/ELT orchestration, and distributed computing concepts.
• Proficiency with Collibra Data Quality platform or equivalent data governance and stewardship tools.
• Strong track record working in agile environments, participating in cross-functional teams, and adapting to rapidly evolving project requirements.
• Excellent analytical, problem-solving, and communication skills, with the ability to convey complex technical topics to both technical and non-technical audiences.

• Databricks Certified Data Engineer Associate or Professional
• Python Institute Certifications (PCAP, PCPP)
• Collibra Ranger or Collibra Data Quality Steward Certifications
• Deep understanding of data quality frameworks, methodologies, and industry best practices
• Hands-on experience building automated data quality tests using Python, PySpark, or similar open-source libraries
• Expertise in designing quality validation steps within ETL/ELT data pipelines for large volumes of structured and semi-structured data
• Familiarity with cloud data ecosystems, especially Azure and Databricks
• Proven ability to operationalize and scale data governance using Collibra or comparable tools
• Experience with dashboarding, data visualization, and monitoring tools for real-time data quality tracking
• Strong collaboration, leadership, and mentoring abilities within agile squads or matrix teams
• Knowledge of data privacy, security, and regulatory compliance requirements
• Ability to drive innovation and continuous improvement in data quality processes

• Opportunity to work on cutting-edge data platforms and technologies in a global, multicultural environment
• Collaborative and agile work culture with empowering career growth opportunities
• Competitive remuneration, benefits, and professional certification support
• Access to Capgemini's global learning platforms, mentorship programs, and technology communities
• Exposure to high-impact projects with Fortune 500 clients

Senior Data Quality Analyst – Capgemini

About Capgemini

Capgemini is a global leader in consulting, digital transformation, technology, and engineering services. With a presence in over 50 countries and a strong heritage of innovation, Capgemini enables organizations to realize their business ambitions through an array of services from strategy to operations. Our collaborative approach and a people-centric work culture have made us a partner of choice for clients across industries.

Role Overview

We are seeking a highly skilled Senior Data Quality Analyst with a robust background in designing, implementing, and maintaining data quality frameworks leveraging Python or Collibra. The ideal candidate will be adept at ensuring data accuracy, consistency, completeness, and reliability across large-scale cloud-based platforms, especially within Azure Databricks environments. This role requires expertise in automated data quality assurance, a deep understanding of data governance, and hands-on experience integrating quality controls into modern data pipelines.

The Senior Data Quality Analyst will be embedded within an agile squad dedicated to a specific business mission while contributing to a broader program comprising 4 to 8 interconnected squads. Collaboration, technical leadership, and a continuous improvement mindset are essential as you work cross-functionally to elevate the organization's data quality standards.

Key Responsibilities

1. Development & Integration

• Design, develop, and implement automated data quality checks using Python scripts and libraries or Collibra Data Quality components.
• Integrate data quality validation logic within existing ETL/ELT pipelines operating on Azure Databricks, ensuring quality gates are consistently enforced across all data flows.
• Develop and maintain reusable Python modules that perform anomaly detection, schema validation, and rule-based data quality checks to enable rapid scaling of quality coverage.
• Collaborate with data engineering teams to embed continuous quality controls throughout the data ingestion, transformation, and consumption lifecycle.
• Support the deployment and management of Collibra-based data quality solutions to automate governance workflows and stewardship activities.

2. Data Quality Management

• Define, measure, and rigorously enforce data quality metrics, thresholds, and Service Level Agreements (SLAs) tailored to business-critical datasets.
• Utilize Collibra to manage and operationalize data governance workflows, maintain business glossaries, and delineate stewardship responsibilities.
• Monitor the integrity of data pipelines for completeness, accuracy, timeliness, and consistency across distributed and cloud-native environments.
• Conduct detailed root cause analyses for complex data quality issues, collaborating with engineers and domain experts to drive permanent remediation and prevention strategies.
• Implement and continuously refine monitoring frameworks, utilizing dashboards and alerting systems (built using Python and Collibra integrations) for real-time visibility into key data quality indicators.

3. Support & Operations

• Act as a Level 2/3 escalation point for data quality incidents, troubleshooting issues and coordinating with other agile squads and technical teams for rapid resolution.
• Work closely with product owners, business analysts, and key stakeholders to understand evolving data requirements and ensure quality expectations are aligned and met.
• Maintain and optimize operational dashboards for ongoing data quality monitoring, leveraging both Python-based and Collibra-integrated solutions.
• Participate actively in agile ceremonies, including sprint planning, daily standups, reviews, and retrospectives, contributing to squad goals and continuous delivery improvements.

4. Governance & Best Practices

• Establish, document, and evangelize data quality standards, validation frameworks, and best practices across squads and the broader data organization.
• Maintain comprehensive documentation on validation rules, automated test cases, and quality assurance procedures, ensuring transparency and repeatability.
• Mentor, coach, and upskill junior data engineers and analysts in data quality concepts, tools, and processes to foster a quality-first culture.
• Ensure strict compliance with data governance, privacy, and security policies by leveraging Collibra's governance and stewardship frameworks.
• Continuously assess emerging technologies, tools, and methodologies for potential enhancement of the data quality ecosystem.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Management, Information Systems, or a closely related field.
• Years of progressive experience in data quality engineering, data management, or related data roles within complex technology environments.
• Demonstrable expertise in Python, including the development of reusable data quality and validation libraries.
• Extensive hands-on experience with Azure Databricks, including cloud-native data processing, ETL/ELT orchestration, and distributed computing concepts.
• Proficiency with Collibra Data Quality platform or equivalent data governance and stewardship tools.
• Strong track record working in agile environments, participating in cross-functional teams, and adapting to rapidly evolving project requirements.
• Excellent analytical, problem-solving, and communication skills, with the ability to convey complex technical topics to both technical and non-technical audiences.

Preferred Certifications (One or More)

• Databricks Certified Data Engineer Associate or Professional
• Microsoft Certified: Azure Data Engineer Associate
• Python Institute Certifications (PCAP, PCPP)
• Collibra Ranger or Collibra Data Quality Steward Certifications

Key Skills & Competencies

• Deep understanding of data quality frameworks, methodologies, and industry best practices
• Hands-on experience building automated data quality tests using Python, PySpark, or similar open-source libraries
• Expertise in designing quality validation steps within ETL/ELT data pipelines for large volumes of structured and semi-structured data
• Familiarity with cloud data ecosystems, especially Azure and Databricks
• Proven ability to operationalize and scale data governance using Collibra or comparable tools
• Experience with dashboarding, data visualization, and monitoring tools for real-time data quality tracking
• Strong collaboration, leadership, and mentoring abilities within agile squads or matrix teams
• Knowledge of data privacy, security, and regulatory compliance requirements
• Ability to drive innovation and continuous improvement in data quality processes

What We Offer

• Opportunity to work on cutting-edge data platforms and technologies in a global, multicultural environment
• Collaborative and agile work culture with empowering career growth opportunities
• Competitive remuneration, benefits, and professional certification support
• Access to Capgemini's global learning platforms, mentorship programs, and technology communities
• Exposure to high-impact projects with Fortune 500 clients

Job Title: Data Quality Specialist

About the Role:

We are seeking a skilled professional to join our team as a Data Quality Specialist. This role is responsible for ensuring the accuracy, consistency, and completeness of data across large-scale cloud-based platforms.

Key Responsibilities:

• Data Quality Engineering

• Design, develop, and implement automated data quality checks using Python scripts and libraries or Collibra Data Quality components.

• Integrate data quality validation logic within existing ETL/ELT pipelines operating on Azure Databricks, ensuring quality gates are consistently enforced across all data flows.

• Develop and maintain reusable Python modules that perform anomaly detection, schema validation, and rule-based data quality checks to enable rapid scaling of quality coverage.

• Collaborate with data engineering teams to embed continuous quality controls throughout the data ingestion, transformation, and consumption lifecycle.

• Support the deployment and management of Collibra-based data quality solutions to automate governance workflows and stewardship activities.

Data Quality Management

• Define, measure, and rigorously enforce data quality metrics, thresholds, and Service Level Agreements (SLAs) tailored to business-critical datasets.

• Utilize Collibra to manage and operationalize data governance workflows, maintain business glossaries, and delineate stewardship responsibilities.

• Monitor the integrity of data pipelines for completeness, accuracy, timeliness, and consistency across distributed and cloud-native environments.

• Conduct detailed root cause analyses for complex data quality issues, collaborating with engineers and domain experts to drive permanent remediation and prevention strategies.

• Implement and continuously refine monitoring frameworks, utilizing dashboards and alerting systems (built using Python and Collibra integrations) for real-time visibility into key data quality indicators.

Required Skills and Qualifications

• Education: Bachelor's or Master's degree in Computer Science, Data Management, Information Systems, or a closely related field.
• Experience: Years of progressive experience in data quality engineering, data management, or related data roles within complex technology environments.
• Technical Skills: Demonstrable expertise in Python, including the development of reusable data quality and validation libraries. Extensive hands-on experience with Azure Databricks, including cloud-native data processing, ETL/ELT orchestration, and distributed computing concepts.
• Collibra: Proficiency with Collibra Data Quality platform or equivalent data governance and stewardship tools.
• Azure Databricks: Strong track record working in agile environments, participating in cross-functional teams, and adapting to rapidly evolving project requirements.
• Problem-Solving and Communication: Excellent analytical, problem-solving, and communication skills, with the ability to convey complex technical topics to both technical and non-technical audiences.

Benefits

• Opportunity to work on cutting-edge data platforms and technologies in a global, multicultural environment.
• Collaborative and agile work culture with empowering career growth opportunities.
• Competitive remuneration, benefits, and professional certification support.
• Access to Capgemini's global learning platforms, mentorship programs, and technology communities.
• Exposure to high-impact projects with Fortune 500 clients.

Preferred Certifications

• Databricks Certified Data Engineer Associate or Professional.
• Microsoft Certified: Azure Data Engineer Associate.
• Python Institute Certifications (PCAP, PCPP).
• Collibra Ranger or Collibra Data Quality Steward Certifications.

Key Skills and Competencies

• Deep understanding of data quality frameworks, methodologies, and industry best practices.
• Hands-on experience building automated data quality tests using Python, PySpark, or similar open-source libraries.
• Expertise in designing quality validation steps within ETL/ELT data pipelines for large volumes of structured and semi-structured data.
• Familiarity with cloud data ecosystems, especially Azure and Databricks.
• Proven ability to operationalize and scale data governance using Collibra or comparable tools.
• Experience with dashboarding, data visualization, and monitoring tools for real-time data quality tracking.
• Strong collaboration, leadership, and mentoring abilities within agile squads or matrix teams.
• Knowledge of data privacy, security, and regulatory compliance requirements.
• Ability to drive innovation and continuous improvement in data quality processes.

The Dubai Health Authority (DHA) oversees the health sector in Dubai and aims to provide an accessible, effective, and integrated healthcare system, in line with the Dubai Strategic Plan 2026. The DHA operates healthcare facilities including hospitals, specialty centers, and primary health centers throughout Dubai, with a focus on quality, efficiency, patients, and staff satisfaction.

This is a full-time on-site role for a Data Quality Analyst at Dubai Health Authority. The Data Quality Analyst will be responsible for data quality, data governance, analytical skills, data management, and data analytics tasks to ensure the accuracy and reliability of healthcare data.

• Data Quality, Data Governance, and Data Management skills
• Analytical Skills and Data Analytics expertise
• Experience in healthcare data analysis and management
• Strong attention to detail and problem-solving abilities
• Excellent communication and teamwork skills
• Bachelor's degree in Data Science, Computer Science, Information Management, or a related field

• Entry level

• Full-time

• Information Technology

• Hospitals and Health Care

The job holder is responsible for leading the design, development, and implementation of the Data Governance program, specifically those relating to data quality as part of the Data Governance Office. They are accountable for maintaining direction and ensuring alignment with business objectives regarding how data is managed across the organization.

The job holder is also a key member of the broader data management group across the organization and is expected to play an important role in influencing and providing direction to the wider data management community.

• Lead the development of the organizational Data Strategy as well as data management in line with strategic business objectives and FAB cultures and values.
• Manage and support the AVP data governance and data quality in the development and oversight of data governance framework standards, practices, policies, and processes.
• Lead the development of the Data Governance Office as a center of excellence committed to ingraining a data-driven decision-making culture across the organization, teaming with external partners and offering end-to-end data services across business and support groups.
• Lead and provide direction in the monitoring and analysis of the latest strategic technological and regulatory trends within the organization and on a global scale.
• Promote good data quality practices and the management of data as a strategic asset.

• Lead the production of information on performance and quality standards for data within the organization.
• Gather and create inputs for the management and reporting of data SLA and KPIs, including monitoring of data quality dashboards and SLA breaches, ensuring adherence to agreed SLA targets and demonstrating improvement against agreed targets.
• Lead and provide guidance and all necessary support to the AVP data governance and data quality in managing and resolving data quality issues, providing advice and guidance to all business areas.
• Advise on targets and monitoring standards with stakeholders for data entry and data collection undertaken.
• Responsible for leading/directing the development of DQ measurement/reporting/control capabilities.
• Responsible for leading/directing the development and maintenance of data quality rules.
• Responsible for leading/directing the development and maintenance of DQ profiling tools/methodologies.
• Responsible for leading the development and ongoing maintenance of data definitions, standards, lineage, and other data quality artifacts as part of the data catalog.
• Lead the development, maintenance, and management of organizational reference data.
• Provide subject matter expertise on systems/process developments to control and improve data quality.
• Lead the development of Data Quality Monitoring tools and DQ Dashboards and provide direction to subordinates.
• Support and guide the RCA team with analyzing data across applications from a Data Quality standpoint.
• Guide and provide necessary support to different Business units from a DQ point of view.

Internal:

• The role requires establishing strong working relationships with all business groups and support functions of the organization at various levels to ensure continued buy-in for the Data Governance Model.

External:

• The role requires regular interactions with vendors, data partners, consulting partners, and regulatory and governmental bodies.

• Delivery against planned DQ roadmap activities.
• # Outstanding high criticality data issues.
• Increase in stakeholder opinion of DQ.
• Improvement in DQ for key data elements.
• Feedback from peers, management, and key stakeholders.
• Demonstrate leadership and guide/monitor subordinates on technical activities and deliveries.

Qualifications:

• Degree educated with a minimum of 3 to 4 years of direct experience; 5 years overall industry experience.

• Minimum 3 to 4 years of direct experience in data-related programs, ideally in financial services.
• Experience of contributing to regulatory projects would be beneficial.
• Strong Data Governance skills; direct experience of developing Data Governance frameworks and/or performing a Data Governance Management role.
• Good operational knowledge of data quality management processes.
• Experience of collating, designing, and presenting top quality management information to senior leadership stakeholders.
• Excellent track record of delivering on strategic data initiatives.

• Good knowledge of Data Governance and Data Quality programs, frameworks, policies, and procedures.
• Experience working on strategic programs and synthesizing business requirements and priorities with existing organizational capabilities.
• Good knowledge of common DQ and dashboard tooling.
• Technical knowledge of common DQ tools and standards such as Informatica EDQ and Oracle EDQ.
• Good SQL knowledge.

• A reliable and trustworthy person able to anticipate and deal with the varying needs and concerns of numerous stakeholders, adapting personal style accordingly.
• Adaptable and knowledgeable, able to discuss a variety of data management situations with both IT and business stakeholders.

Remote Work:

No

Employment Type:

Full-time

Lead Data Quality Expert

The ideal candidate will be responsible for leading the development and implementation of data governance programs, focusing on data quality.

They will maintain direction and ensure alignment with business objectives regarding how data is managed across the organization.

• Develop a comprehensive data strategy in line with strategic business objectives.
• Manage and support the development of data governance framework standards, practices, policies, and processes.
• Lead the development of the Data Governance Office as a center of excellence committed to ingraining a data-driven decision-making culture.

• Develop information on performance and quality standards for data within the organization.
• Monitor and analyze data quality dashboards and SLA breaches, ensuring adherence to agreed SLA targets.
• Provide guidance and support to stakeholders in managing and resolving data quality issues.
• Advise on targets and monitoring standards with stakeholders for data entry and data collection undertaken.
• Develop DQ measurement/reporting/control capabilities.
• Maintain data quality rules and develop DQ profiling tools/methodologies.
• Develop and maintain data definitions, standards, lineage, and other data quality artifacts.

• Degree educated with a minimum of 3 to 4 years of direct experience; 5 years overall industry experience.
• Minimum 3 to 4 years of direct experience in data-related programs, ideally in financial services.
• Strong Data Governance skills and good operational knowledge of data quality management processes.
• Experience of collating, designing, and presenting top-quality management information to senior leadership stakeholders.
• Excellent track record of delivering on strategic data initiatives.

• A reliable and trustworthy person able to adapt personal style to meet the needs of numerous stakeholders.
• Adaptable and knowledgeable, able to discuss various data management situations with both IT and business stakeholders.

Quality Lead