National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Governance Manager

Smart Recruiters
Greater London
5 days ago
Create job alert

Job Description

The Data Governance Manager is responsible for leading the development and implementation of the organization's data governance strategy. This role ensures the integrity, quality, and security of data across the enterprise, while also driving compliance with regulatory requirements and supporting business objectives. The new role will be responsible for managing company-wide data governance activities. Head of DG is responsible for developing and implementing data governance policies, monitoring adherence to data standards, and providing guidance on data management practices. This role involves ensuring data quality, consistency, and security across entire organization.

Key Challenges:

Understanding the Business Value of Data Governance: Demonstrating how data governance enhances data quality and supports informed business decisions is crucial. Hance, ensuring that data governance is seen as a strategic asset rather than just a compliance requirement.

Clarifying Ownership and Responsibility: Effective data governance requires collaboration across business units, with clear roles and responsibilities for data management. Head of DG is responsible to coordinate Data Communities.

Ensuring Data Quality: Maintaining high data quality is a continuous challenge. This involves implementing data validation checks, data cleaning processes, and regular audits to ensure data accuracy and reliability. Addressing issues related to inaccurate, incomplete, or inconsistent data.

Compliance with Regulations: Keeping up with evolving data protection regulations and ensuring compliance such as GDPR and SOX. That requires constant vigilance and adaptation of data governance frameworks.

Data Governance Framework: This involves implementing policies, standards, rules and procedures around data governance. Integrating data from various sources while maintaining consistency and quality can be complex. Effective data governance frameworks are needed to manage this integration.

Tracking Data Lineage: Ensuring accurate tracking of data's origin, movement, and transformations across the organization.

Managing Siloed Data: Breaking down data silos and ensuring data integration across departments.

Cultural Change - Promoting a Data-Driven Culture: Encouraging a culture where data governance is valued and practiced by everyone in the organization. Promoting a data-driven culture within the organization can be challenging. It requires ongoing training and awareness programs to ensure employees understand the importance of data governance and their roles in it.

 

 

Key Responsibilities:

  • Strategic Leadership: Develop and execute a comprehensive data governance strategy that aligns with the organization's goals and regulatory requirements.
  • Policy Development:  Provide guidance on data lifecycle management, data contract, data privacy, and data security. Establish and enforce data governance policies, standards, and procedures to ensure data quality, security, and compliance.
  • Data Quality Management: Oversee data quality initiatives, including data profiling, cleansing, and remediation efforts to ensure accurate and reliable data. Oversee data quality initiatives to maintain accurate, consistent, and reliable data. Analyze and address data-related issues, identifying opportunities for improvement.
  • Stakeholder Collaboration: Collaborate with senior leaders, business units, privacy team and IT teams to promote data governance best practices and ensure alignment with business objectives.
  • Implementation of Data Governance Tools: Select, implement, and manage data governance tools and technologies to support data governance initiatives and ensure efficient data management.
  • Regulatory Compliance: Ensure compliance with data privacy and protection regulations such as SOX and GDPR by implementing robust data governance frameworks.
  • Data Communities: Lead the data stewardship program, assigning roles and responsibilities for data management across the organization.
  • Training and Awareness: Develop and deliver training programs to educate employees on data governance policies, procedures, and best practices.
  • Performance Monitoring: Implement metrics and reporting mechanisms to monitor the effectiveness of data governance initiatives and drive continuous improvement.

Qualifications:

  • Education: Bachelor's degree in IT Service Management, Computer Science, or a related field. A Master's degree or relevant certifications (e.g., PMP, CDMP) are highly desirable.
  • Experience: Proven experience in data governance, data management, data compliance and project management or a related field, with a proven track record at a senior level. Knowledge of industry regulations such as GDPR and SOX.
  • Skills: Strong understanding of data governance frameworks, data quality management, data security, and privacy regulations. Excellent leadership, communication, and project management skills. Strong understanding of data quality, metadata management, and data security. Ability to work collaboratively with cross-functional teams

 

Additional information

At Sportradar, we celebrate our diverse group of hardworking employees. Sportradar is committed to ensuring equal access to its programs, facilities, and employment opportunities. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We encourage you to apply even if you only meet most of the requirements (but not 100% of the listed criteria) – we believe skills evolve over time. If you’re willing to learn and grow with us, we invite you to join our team!


Additional Information

At Sportradar, we celebrate our diverse group of hardworking employees. Sportradar is committed to ensuring equal access to its programs, facilities, and employment opportunities. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We encourage you to apply even if you only meet most of the requirements (but not 100% of the listed criteria) – we believe skills evolve over time. If you’re willing to learn and grow with us, we invite you to join our team!

Related Jobs

View all jobs

Data Governance Manager

Data Governance Manager

Data Governance Manager

Data Governance Manager

Data Governance Manager

Data Governance Manager

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs Skills Radar 2026: Emerging Tools, Languages & Platforms to Learn Now

The UK’s data science job market is evolving fast—from forecasting models and AI assistants to real-time decision systems. In 2026, data scientists aren’t just expected to build models—they’re responsible for shaping insights that fuel everything from patient care to predictive banking. Welcome to the Data Science Jobs Skills Radar 2026—your essential annual guide to the languages, tools, and platforms driving demand across the UK. Whether you’re entering the job market or reskilling mid-career, this roadmap helps you prioritise the skills that matter most right now.

How to Find Hidden Data Science Jobs in the UK Using Professional Bodies like the RSS, BCS & More

The data science job market in the UK is thriving—but also increasingly competitive. As organisations in finance, healthcare, retail, government, and tech accelerate digital transformation, the demand for data talent has soared. Yet many of the best data science jobs are never posted publicly. They’re shared behind closed doors—within professional networks, at invite-only events, or through member-only mailing lists and specialist interest groups. These “hidden” roles are often filled through referrals, collaborations, or direct outreach to trusted experts. In this guide, we’ll show you how to unlock these hidden opportunities by engaging with key UK professional bodies such as the Royal Statistical Society (RSS), BCS (The Chartered Institute for IT), and Turing Society, plus communities like PyData and AI UK. You’ll learn how to use directories, CPD events, and networks to move beyond job boards—and into roles where you’re approached, not just applying.

How to Get a Better Data Science Job After a Lay-Off or Redundancy

Redundancy can be tough to face, especially in a competitive field like data science. But it’s important to know: your experience, analytical thinking, and modelling skills are still in demand. Across sectors like healthcare, finance, e-commerce, government and AI startups, UK employers continue to seek data scientists who can deliver value through insight, prediction, and automation. This guide will walk you through how to bounce back from redundancy with purpose and clarity—whether you're a data analyst looking to step up, a mid-level data scientist, or a machine learning specialist seeking a better-aligned opportunity.