Data Domain Lead

Data Domain Lead

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