À propos de ce poste Data Domain Lead chez Marsh
Company:
MercerDescription:
Marsh is seeking a Data Domain Lead to drive the strategy, development, and adoption of enterprise data products within an assigned domain. This role will serve as the single accountable leader for turning domain data into trusted, reusable, and business-ready products that support operational processes, analytics, reporting, and AI use cases.
The ideal candidate will combine strong business acumen with data leadership experience, partnering across business, technology, architecture, governance, and regional teams to define domain priorities, establish authoritative business definitions, and deliver measurable business value. This is a highly cross-functional role that requires a product mindset, strong stakeholder engagement, and the ability to translate business needs into scalable, governed data solutions.
What can you expect?
A strategic opportunity to shape enterprise data products that support critical business processes and decisions
Visibility across business, technology, and regional leadership teams
A highly collaborative role working across architecture, engineering, governance, and operational stakeholders
The ability to influence how data is trusted, reused, and activated across the organization
An environment focused on business outcomes, measurable value, and enterprise-scale transformation
What is in it for you?
A key leadership role in advancing Marsh McLennan’s enterprise data strategy
The opportunity to drive real business impact through data product adoption and value realization
Collaboration with global colleagues and cross-functional teams
Exposure to enterprise architecture, governance, analytics, and AI initiatives
A culture that values innovation, collaboration, and continuous improvement
We will count on you to:
Own the strategy, roadmap, and measurable outcomes for an assigned data domain
Define domain scope, boundaries, and authoritative business definitions
Translate business needs into reusable, governed domain data products
Partner with business sponsors, architects, engineers, and governance teams to deliver domain capabilities
Manage the domain backlog, release priorities, and product acceptance criteria
Ensure the domain supports end-to-end business processes, not just individual systems or datasets
Lead tracer testing across real business transactions to validate data quality, handoffs, identifiers, and usability
Drive adoption across operational applications, reporting, analytics, self-service, and AI capabilities
Establish quality, governance, privacy, and control requirements within the product lifecycle
Coordinate delivery across global and regional teams, including dependencies, milestones, and risks
Measure domain success through trust, reuse, adoption, and business value
Escalate unresolved issues related to ownership, quality, capacity, and priorities
What you need to have:
Significant experience in data products, enterprise data, business data strategy, product management, or domain leadership
Strong knowledge of business process design and translation of business needs into data requirements
Experience delivering data capabilities into production and driving adoption with business stakeholders
Working knowledge of data architecture, data modeling, metadata, quality, governance, and integration
Strong stakeholder management skills across business, technology, operations, and regional teams
Proven ability to lead cross-functional initiatives without relying solely on direct authority
Strong prioritization, problem-solving, and decision-making skills
Excellent communication skills with the ability to explain complex data topics in clear business language
Ability to operate effectively in ambiguity while driving measurable outcomes
What makes you stand out?
Experience in insurance, risk, benefits, financial services, or another complex regulated industry
A product-oriented mindset with a strong focus on adoption, value realization, and business outcomes
Experience balancing enterprise consistency with regional and business-specific requirements
Demonstrated success in identifying and resolving data handoff, ownership, and quality issues across end-to-end processes
Familiarity with data activation across analytics, reporting, operational platforms, and AI use cases