Senior Data Governance Manager

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We’re an AI‑first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving.

The customer is one of the largest online gambling companies in the world, with over 26 million clients across all markets. The company was founded in 1997 and listed on Nasdaq Stockholm in 2004. They are committed to offering their clients the best possible deal and user experience, while ensuring a safe and fair gambling environment.

• Define and advance a modern data governance vision aligned with our Data, AI, and automation strategy
• Partner with senior stakeholders to ensure governance accelerates value creation, and champion a culture where automation, explainability, and trust are strategic enablers

• Establish enterprise‑wide standards for the semantic layer and govern the creation of consistent business data models, master data, and metrics
• Ensure models integrate with metadata and lineage tools for discoverability and explainability
• Partner with Analytics, Engineering, and Platform teams to ensure scalable, AI‑ready models that support generative AI use cases like natural‑language queries and text‑to‑SQL
• Assess governance maturity and drive continuous improvements that automate workflows and accelerate trusted data delivery

• Embed governance into AI pipelines to ensure models use trusted, explainable, lineage‑rich data
• Partner with AI/ML teams to support LLMOps, RAG, and agent‑based systems, and define guardrails for transparent, ethical, and reliable use of data and semantic models in generative AI

• Oversee the enterprise data catalog and lineage systems to ensure full transparency across ingestion, transformation, and consumption
• Provide rich, connected metadata linking datasets, semantic models, AI models, pipelines, and policies for both human and AI use
• Automate data quality monitoring and lineage capture to support explainable AI and compliance
• Enable governed self‑service data access and analytics through the semantic layer, balancing user agility with automated controls, and ensure governance policies are seamlessly embedded into the A&I data platform

• Define and enforce governance policies covering access, lifecycle management, security, and privacy
• Translate regulatory obligations (e.g., GDPR, industry‑specific compliance) into actionable, automated controls within the platform
• Align governance with established frameworks (e.g., DAMA‑DMBOK) and embed best practices in stewardship programmes
• Ensure governance frameworks scale across modern data platforms (e.g., AWS) and integrate seamlessly with engineering workflows

• Proven experience in data governance, data management, or data quality leadership roles
• Strong understanding of data governance frameworks (e.g., DAMA‑DMBOK), metadata, data quality, and master data management (MDM)
• Demonstrated expertise in data ethics and regulatory compliance frameworks such as GDPR, with a strong ability to translate these principles into practical data policies and controls
• Strong understanding of modern data platforms and architectures (e.g., AWS) and how governance integrates with engineering workflows
• Hands‑on experience with data cataloguing, metadata management, and lineage tools (e.g., Collibra, Alation, Open Metadata)
• Familiarity with semantic layer concepts and tools (e.g., Cube.js, LookML) and their role in governing metric definitions, data contracts, and AI/analytics consumption
• Experience contributing to or leading data stewardship programmes and fostering a culture of ownership and accountability
• Familiarity with self‑service analytics environments and enabling governed access to data for business…