Data Governance Lead

WPP

WPP is the trusted growth partner for the world’s leading brands.  We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth.    We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise.   Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow.    For more information, visit WPP.com.   Why we're hiring: The Identity, AI and Data Access Governance Lead is responsible for governing who, and what, can access DTS systems, data, APIs, tools, workflows and AI-enabled capabilities. This is a hands-on governance and control role, reporting into the SVP Security and Compliance. The role ensures that access across DTS is appropriate, auditable, reviewed, least-privileged and aligned with security, privacy, compliance and client commitments. The scope covers traditional human access, external users, privileged access, service accounts, machine identities, API keys, tokens, dataset access, and the emerging governance of AI agents and agentic workflows. The role will work closely with Architecture, Security, Product, Engineering, Infrastructure, Privacy, Legal/DPO, TechOps, Enterprise Technology and the ISMS and Risk Officer to ensure DTS has a clear and controlled model for access across platforms such as WPP Open, Choreograph, InfoSum, Open Intelligence, Resolve and related DTS capabilities.   What you'll be doing: 1. IDENTITY AND ACCESS GOVERNANCE FRAMEWORK Define and maintain the access governance framework for DTS. This includes: * Defining access governance standards, processes and control expectations. * Establishing how access should be requested, approved, provisioned, reviewed, revoked and evidenced. * Ensuring access governance covers internal users, external users, clients, partners, vendors, service accounts, machine identities and AI agents. * Aligning identity and access governance with DTS architecture, security, privacy, compliance and data governance requirements. * Ensuring access governance is practical for product and engineering teams to implement.   2. ACCESS REVIEWS AND RECERTIFICATION Own the process for regular access reviews and recertification across DTS. This includes: * Defining the scope, frequency and evidence requirements for access reviews. * Coordinating access reviews for critical DTS systems, production environments, privileged roles, sensitive datasets, client-facing platforms and administrative tools. * Ensuring access review outcomes are tracked, remediated and evidenced. * Identifying stale, excessive, orphaned or poorly owned access. * Escalating overdue, high-risk or unresolved access issues through the appropriate governance channels.   3. PRIVILEGED ACCESS GOVERNANCE Ensure privileged access across DTS is properly controlled, justified and auditable. This includes: * Reviewing access to production systems, cloud environments, security tools, databases, CI/CD tooling, administrative consoles and sensitive platforms. * Supporting least-privilege, just-in-time and time-bound access models where appropriate. * Working with Cloud and Platform Security and Infrastructure to improve privileged access controls. * Ensuring privileged access risks are visible in the DTS risk register where required.   4. EXTERNAL USER, CLIENT AND PARTNER ACCESS GOVERNANCE Govern access for external users, clients, agencies, partners and vendors. This includes: * Defining standards for external user onboarding, approval, permissions, expiry and offboarding. * Ensuring external access has a clear business owner and justification. * Supporting access governance across client workspaces, agency environments, partner integrations and shared collaboration areas. * Working with Product and Engineering to ensure tenant, workspace and client-level isolation is appropriately governed. * Tracking risks related to stale accounts, vendor access, partner permissions and external user overprivilege.   5. SERVICE ACCOUNT, MACHINE IDENTITY AND API ACCESS GOVERNANCE Govern non-human access across DTS systems and platforms. This includes: * Defining standards for service accounts, machine identities, automation users, API keys, tokens, secrets and integration credentials. * Ensuring non-human access has clear ownership, purpose, scope, rotation, expiry and auditability. * Working with Product, Engineering, Cloud Security and Infrastructure to reduce unmanaged credential risk. * Ensuring service accounts and machine identities are included in access reviews. * Supporting stronger governance of API access, token issuance, credential lifecycle and integration permissions.   6. AI AND AGENTIC ACCESS GOVERNANCE Define and oversee the governance model for AI agents and agentic workflows across DTS. This includes: * Defining how AI agents are identified, permissioned, monitored, reviewed and revoked. * Ensuring agents have clear ownership, scoped permissions and auditable actions. * Defining which agent actions require human approval or additional control. * Governing agent access to APIs, tools, datasets, workflows, client environments and production capabilities. * Ensuring agents act within delegated authority and cannot exceed the permissions of the user, system or business process they represent. * Working with Product, Architecture and Security to ensure agentic workflows are designed with clear action boundaries. * Working with the Product, Application and Offensive Security Lead to test whether agent permissions and action boundaries can be bypassed. * Working with Privacy Engineering to ensure AI access models support permitted use, minimisation and data protection requirements. 7. DATA ACCESS GOVERNANCE Govern access to sensitive, client, partner and WPP-owned data across DTS. This includes: * Defining standards for dataset access approval, review, revocation and evidence. * Supporting data classification from an access-control and security-governance perspective. * Ensuring access to sensitive data is role-based, purpose-based, least-privileged and auditable. * Supporting controls for cross-client, cross-market, cross-agency and partner data access. * Ensuring data access governance supports InfoSum, Open Intelligence, Resolve, WPP Open and other DTS data collaboration use cases. * Working with Privacy Engineering on data minimisation, permitted use, retention and privacy-by-design requirements. * Ensuring data access risks are surfaced through the DTS risk process.   8. GOVERNANCE OF ACCESS TO TOOLS, WORKFLOWS AND ACTIONS Ensure access governance extends beyond systems and datasets into tools, workflows and actions. This includes: * Defining governance for access to operational tools, workflow automation, orchestration systems, AI tools and administrative actions. * Ensuring high-risk actions are subject to appropriate approval, logging and monitoring. * Supporting segregation of duties across sensitive workflows. * Ensuring automated workflows and agents have clearly scoped authority. * Working with Security Operations to ensure high-risk access and actions are visible in monitoring and detection processes.   9. AUDITABILITY, EVIDENCE AND REPORTING Maintain clear evidence of access governance and support audit and assurance requirements. This includes: * Producing access governance evidence for SOC 2, ISO 27001, client assurance, internal audit and risk reviews. * Working with the ISMS and Risk Officer to ensure access controls, reviews, exceptions and remediation actions are documented. * Reporting on access review completion, high-risk access, overdue actions and access control gaps. * Supporting client and audit questions related to identity, access, privileged roles, service accounts, AI agents and data access. * Ensuring access governance is repeatable, measurable and auditable.   Who you'll be working with: The Identity, AI and Data Access Governance Lead will be accountable for: * DTS identity and access governance standards. * Regular access reviews and recertification. * Privileged access governance. * External user, client, partner and vendor access governance. * Service account, machine identity, API key and token governance. * AI agent identity, permission and action governance. * Dataset and sensitive data access governance. * Governance of access to tools, workflows and high-risk actions. * Access governance evidence for audit, compliance and client assurance. * Escalation of material access risks into the DTS risk process.   What you'll need: The successful candidate will have: * Experience in identity governance, access management, IAM, security governance, GRC, data access control or platform security. * Strong understanding of least privilege, role-based access control, attribute-based access control, access reviews, privileged access and segregation of duties. * Experience governing access across SaaS platforms, cloud environments, APIs, data platforms or enterprise technology estates. * Knowledge of identity platforms such as Okta, Auth0, Keycloak, Azure AD / Entra ID or similar. * Understanding of service accounts, machine identities, API keys, tokens, secrets and non-human access governance. * Understanding of AI agents, agentic workflows, delegated authority and tool-access governance would be highly valuable. * Understanding of data classification, dataset access governance, privacy-by-design and audit requirements. * Ability to work across security, architecture, product, engineering, infrastructure, legal, privacy and compliance teams. * Strong organisational skills and ability to coordinate reviews, evidence, remediation and reporting. * Ability to translate complex access issues into clear risks, controls and practical actions.   LEADERSHIP EXPECTATIONS The Identity, AI and Data Access Governance Lead is expected to: * Be structured, disciplined and pragmatic. * Bring clarity to complex access and permission models. * Challenge excessive, unclear or poorly governed access. * Work constructively with product and engineering teams to design workable controls. * Avoid creating unnecessary bureaucracy while ensuring access is properly governed. * Treat human, machine and agent access as part of the same control landscape. * Escalate material access risks clearly and early. * Support DTS in building a secure, auditable and scalable access governance model.   SUCCESS MEASURES Success in the role will be measured by: * DTS having clear identity, access and data access governance standards. * Regular access reviews completed on schedule with evidence. * Reduction in stale, excessive, orphaned or poorly owned access. * Stronger governance of privileged access and production access. * Clear ownership and review of service accounts, machine identities, API keys and tokens. * Defined governance for AI agent identities, permissions and actions. * Improved auditability of access to data, APIs, tools, workflows and production systems. * Better alignment between identity, security, privacy, architecture, product and engineering teams. * Material access risks being visible through the DTS risk register and Risk Review Board. * Increased confidence that DTS can answer: who or what has access to what, why, and when was it last reviewed? Who you are: You're open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working. You're optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected. You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.   What we'll give you: Passionate, inspired people – We aim to create a culture in which people can do extraordinary work. Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry. Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge? #LI-Hybrid  We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. WPP is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers. PLEASE READ OUR PRIVACY NOTICE (HTTPS://WWW.WPP.COM/EN/CAREERS/WPP-PRIVACY-POLICY-FOR-RECRUITMENT) FOR MORE INFORMATION ON HOW WE PROCESS THE INFORMATION YOU PROVIDE.

Securitas

Securitas Group Securitas is a world-leading safety and security solutions partner that helps make your world a safer place. With nine decades of deep experience means we see what others miss. By leveraging technology in partnership with our clients, combined with an innovative, holistic approach, we’re transforming the security industry. With 322 000 employees in 44 markets, we see a different world and create sustainable value for our clients by protecting what matters most - their people and assets. Securitas IT in AMEA Securitas IT in AMEA deliver IT-services to our 12 countries within the region. We provide the technology needed to fulfill the Securitas business strategy to be client centric, data driven, and people focused. We transform, build and protect our IT landscape in a professional and cost-efficient way. We are a diverse and inclusive team that all help each other out and have a great deal of fun together. ---------------------------------------------------------------------------------------------------------------------------------- Role overview We are seeking an experienced and driven Data/BI Manager (Finance & Operations) to lead the reporting and data enablement function, bridging the gap between our requirements from our countries and divisional functions (including Finance, People/HR and IT) users and technical data teams. This role will translate business needs into actionable data solutions, manage end-to-end reporting delivery, ensure data quality and compliance, and guide the team of data analysts and engineers. A key aspect of this role will be to recruit, build, and lead a high-performing data reporting team, establishing scalable processes and robust governance for long-term success. The ideal candidate combines strong technical data capabilities with a deep understanding of Finance KPIs, compliance, and reporting needs. He/she will act as a Strategic Data Partner to become a bridge between business goals and technical execution, focusing on maximizing value by prioritizing critical requirements. ---------------------------------------------------------------------------------------------------------------------------------- Responsibilities 1. Reporting and Analytics • Translate Finance business needs into data & reporting requirements. • Design intuitive and interactive dashboards using Power BI. • Analyze financial data for trends, variances, and insights to support business strategy. • Present findings and recommendations to stakeholders, Finance leadership, and cross-functional teams. 2. Business-Technology Interface • Serve as the primary liaison between our country and divisional stakeholders and technical data teams • Convert business objectives into detailed functional and technical specifications. • Review and validate data models, source-to-target mappings, and metric definitions. • Ensure proper implementation by collaborating closely with data engineers and BI developers. 3. Data Management and Governance • Lead initiatives on data quality, lineage, consistency, and regulatory compliance (e.g., GDPR). • Establish and enforce data governance policies, processes, and metadata standards, in alignment with the Global IT guardrails. • Conduct root cause analysis for data issues and define quality rules and reconciliation frameworks. • Oversee the data lifecycle management across source systems, warehouses, and reporting layers. 4. Team Leadership and Collaboration • Manage and mentor a team of data analysts, report developers, and data engineers. • Promote collaboration, resolve escalations, and drive continuous improvement in data practices. • Foster a culture of transparency, documentation, and knowledge sharing. Make feedback part of that culture to grow your way of working and your team members • Develop project plans, ensure executing efficiency • Roadmap to achieve department goals • Stakeholder collaboration – bridge between the different departments for a smooth coordination (IT, HR, Finance) across the different countries of the team members 5. Technical Oversight • Understand end-to-end data flows, system integrations, and data architecture. • Oversee development of data pipelines and cloud-based infrastructure (Azure preferred). • Support DevOps and CI/CD-based deployment for reporting and data assets. • Collaborate with IT for performance optimization, platform upgrades, and solution scalability. ---------------------------------------------------------------------------------------------------------------------------------- Requirements * 6+ years of experience in data analytics, BI/reporting including 2+ years in data management roles. * Demonstrated success in Finance reporting transformation. Reporting within sales and HR is advantageous. * Strong knowledge of Finance processes, KPIs, and regulatory reporting. * Demonstrated success in building reporting teams. * Hands-on experience with reporting platforms (Power BI), data modelling, and cloud architecture (Azure Data Factory) * Proficiency in SQL and familiarity with scripting (Python preferred). * Experience working in Agile/Scrum environments and leading delivery in distributed teams. * Proven track record of driving team initiatives to meet company goals and fostering a culture of accountability. * Demonstrated ability to mentor, motivate, and develop high-performing teams. * Extensive experience working with cross-functional teams to deliver complex projects. * Excellent interpersonal, verbal, and written communication skills to influence stakeholders at all levels. * Excellent verbal and written English; ability to present and influence at all levels. * Prior experience in working with ERP (Dynamics), Finance and HR applications is a plus. Core Skills and Competencies Technical • SQL, Python, Advanced Excel • Power BI (Visualization) and Fabric features • Fabric Knowledge: Understand Lakehouse architecture, OneLake, Dataflows, and integration with Synapse and Notebooks. • DAX expertise • Azure DevOps Cloud Platform: Azure preferred • Data Modelling, Metadata Management (Collibra, Databricks) • Data warehousing, Data Lake • CI/CD, ETL/ELT tools (Azure Data Factory, SSIS) Analytical • Financial KPIs (P&L, AP/AR, Cost Centers, Forecasts) • Problem-Solving & Root Cause Analysis • Critical Thinking & Data Interpretation • Statistical & Trend Analysis Leadership and Soft Skills • People management, hiring and team building • Stakeholder Engagement & Communication • Team Leadership & Coaching • Attention to Detail, Time Management • Adaptability & Cross-Functional Collaboration • Needs vs. Wants Assessment: Skilled in prioritizing features based on business value. ---------------------------------------------------------------------------------------------------------------------------------- Working conditions The role is open for candidates based in Gurugram, India. It's a hybrid working model. ---------------------------------------------------------------------------------------------------------------------------------- WHAT WE OFFER At Securitas we believe in doing the right thing and doing it well. For our customers and our employees. Our employees come from all walks of life and bring with them a multitude of talents and perspectives. We aim for diverse representation throughout the company, and we are committed to equal pay, safe working conditions, gender balance and an inclusive work environment with a wide range of skills and development opportunities. If it all sounds good to you, don’t hesitate to apply!

Professional Galaxy AB

Professional Galaxy is an IT and technology consulting company providing highly specialized expertise in IT, software development, SAP, procurement, electronics, and mechanical design. We collaborate with experienced senior experts and deliver strategically valuable competence to some of Sweden’s most complex and analytically demanding projects. Our focus is always on high quality, professionalism, and clear, measurable results. We are seeking a highly skilled Data & AI Governance Consultant to support the review, enhancement, and implementation of our Data & AI governance framework. This role will focus on updating existing governance documentation, identifying and addressing gaps against leading industry standards, designing an improved operating model for data management, and providing hands-on support in implementing a Responsible AI program. The ideal candidate brings deep expertise in AI governance, regulatory frameworks, data management practices, and stakeholder facilitation, combined with strong writing, analytical, and advisory skills. Key Responsibilities: Review & Update AI Governance Documents Conduct a structured review of existing AI governance documents, assessing quality, current state, and alignment to governance principles Lead working sessions with internal teams to gather input, capture gaps, and align required changes Draft revised governance documents ensuring clarity, consistency, and implementation readiness Manage review cycles, incorporate feedback, and prepare final sign-off versions Outcome: Updated and implementation-ready versions of all AI governance documents Identify Gaps & Develop Missing AI Governance Documentation Benchmark existing documentation against key standards and frameworks (e.g., EU AI Act, ISO 42001, NIST AI RMF) Conduct structured gap analysis to identify missing governance components, areas of exposure, and priorities for remediation Develop new governance documents where needed, ensuring alignment with best practices and organizational requirements Present findings and recommendations to stakeholders clearly and actionably Outcome: Comprehensive gap analysis and creation of missing governance artifacts Enhance the Data & AI Governance Operating Model Co-design an improved data management operating model addressing roles, responsibilities, decision rights, processes, and governance structures Document and iterate the proposed model collaboratively with internal teams Support validation and approval of the operating model by senior stakeholders Outcome: A refined data & AI governance operating model ready for adoption Support Implementation of the Responsible AI Program Assess current maturity, scope, and needs of the Responsible AI program Participate in and drive structured implementation sprints to operationalize governance processes (e.g., AI risk assessments, AI reviews, lifecycle controls, tooling input) Conduct enablement workshops to build internal capability and embed Responsible AI practices across teams Provide ongoing advisory support to stakeholders and leadership on Responsible AI governance and strategic decision-making Outcome: Practical, hands-on support enabling effective rollout of Responsible AI across the organization Required Skills & Qualifications: Strong experience in Data Governance, AI Governance, Responsible AI, or related regulatory/compliance roles Knowledge of ML lifecycles, data pipelines, model evaluation, explainability, bias detection, model monitoring, AI security, robustness, and data quality controls Deep knowledge and proven experience of working with AI governance frameworks (EU AI Act, ISO 42001, NIST AI RMF, or equivalents) Demonstrated ability to draft and refine policies, guidelines, and governance documents Experience facilitating workshops, interviews, and cross-functional working sessions Ability to design operating models, governance structures, and organizational processes Excellent communication, analytical, and stakeholder-management skills Ability to work independently and deliver high-quality outputs within agreed timelines Experience in driving federated data governance in data mesh and domain-driven environments Ability to work in a multi-cultural, global environment Application: Are you the right person for this assignment, or would you like to recommend a strong candidate? Please apply directly through our system with: Your updated CV Your availability to start the assignment a In your motivation, describe why you are suitable for this assignment — refer to previous assignments, employment, education, and personal qualities. Please note: Applications via email are not accepted. All applications must be submitted through the portal to be valid. Assignments are offered continuously, so we recommend applying immediately. Öppen för alla Vi fokuserar på din kompetens, inte dina övriga förutsättningar. Vi är öppna för att anpassa rollen eller arbetsplatsen efter dina behov.