We are seeking an experienced Data Manager to lead the strategy, architecture, delivery, and governance of our enterprise data function.
The ideal candidate will bring deep expertise in Commercial P&C insurance data across all lines of business, with particular strength in Auto, General Liability, and Workers Compensation. This leader must combine strong data and platform expertise with business fluency, systems thinking, and the judgment to translate evolving business needs into scalable data structures, semantic layers, reporting models, and trusted outputs.
This role is responsible for building and leading a team that enables a Data-as-a-Service model for the business, empowering FP&A, Actuarial, Underwriting, Operations, and other power users to access the information they need through governed and well-structured data products and reporting environments. The successful candidate must also ensure the enterprise data platform supports inbound and outbound feeds, external reporting needs, and downstream consumption by applications, integrations, and AI capabilities.
This is not a pure oversight role. The successful candidate must be able to operate at both the strategic and technical level — setting direction, enforcing delivery discipline, shaping requirements with the business, and making sound architectural decisions across Microsoft Fabric, semantic models, Power BI, reporting, data exchange, and downstream data consumption patterns. This role will report directly to the CIO and work closely with the leader responsible for applications, integrations, and AI enablement.
This is a highly hands-on leadership role. The successful candidate must be comfortable working directly with the team on data design, semantic layers, reporting structures, troubleshooting, and query refinement when needed to unblock delivery and improve outcomes.F
1.Leadership & Team Management
- Lead and develop a small, high-performing data team (currently offshore), ensuring clear roles, accountability, and focus on high-impact delivery
- Build and operate a Data-as-a-Service (DaaS) model, establishing the structure, processes, and governance needed to enable business stakeholders (e.g., FP&A, Actuarial, Underwriting) to self-serve data in a controlled and scalable manner
- Shape and manage incoming demand, working with business stakeholders to refine requirements, challenge assumptions, and ensure requests are aligned to clearly defined business outcomes
- Ensure business ownership of requirements, including definition of expected outputs, business rules, and acceptance criteria prior to execution
- Lead delivery across a hybrid model of internal resources and external vendor partners, leveraging third-party expertise to support larger or specialized initiatives while maintaining overall accountability for outcomes
- Manage vendor partners and consultants, ensuring clear scope, delivery expectations, quality standards, and effective knowledge transfer to internal team members
2.Technical Execution
- Define and oversee scalable, cost-effective enterprise data architecture using Microsoft Fabric, Power BI, and related technologies to support reporting, analytics, data exchange, and downstream consumption
- Operate as a hands-on technical leader, working directly with the team on data design, semantic layers, reporting structures, troubleshooting, query refinement, and issue resolution as needed to maintain delivery momentum
- Ensure the data platform operates as a structured, scalable enterprise capability, avoiding accumulation of ad hoc or compensating logic that should reside in upstream systems or applications
- Own the design, governance, and publication of semantic layers and business-facing data models that support:
- Power BI reporting and dashboards. pricing models, actuarial and financial analysis underwriting and operational decision-making
- Build and enable a Data-as-a-Service (DaaS) model, with governed data products, reporting models, and semantic layers that allow FP&A, Actuarial, Underwriting, Operations, and other power users to self-serve information in a consistent and scalable manner
- Design and support multiple data consumption patterns, including:
- governed reporting and dashboards through Power BI
- ad hoc and advanced analysis through Fabric Notebooks and related analytical environments
- Define and support architecture for inbound and outbound data integration, including ingestion of external source data and delivery of data feeds required for partner reporting, carrier reporting, external reporting, and other downstream processes
- Ensure the data platform supports both internal DaaS capabilities and external reporting obligations, with structured, reliable, repeatable, and traceable delivery of data to downstream consumers
- Ensure data structures, semantic layers, and reporting models are aligned to business processes, line-of-business context, and intended decision use, with strong understanding of the underlying business meaning of the data
- Oversee end-to-end enterprise data and reporting initiatives, ensuring delivery of trusted, production-ready outputs aligned to clearly defined business objectives
- Drive alignment between upstream systems, integrations, and downstream data/reporting platforms, ensuring business logic is implemented in the appropriate layer and minimizing reliance on the data platform as a compensating mechanism
3.Stakeholder Collaboration
- Work closely with business stakeholders (FP&A, Actuarial, Underwriting, Operations) to translate business questions into clearly defined data outputs, semantic models, reports, and data products
- Ensure requests are framed around the intended business outcome or decision, rather than broad or undefined data pulls
- Partner with stakeholders to define scope, business logic, data definitions, and success criteria prior to execution
- Reinforce and enforce business ownership of requirements, ensuring stakeholders are accountable for defining what is needed and validating that delivered outputs meet expectations
- Guide stakeholders toward the appropriate consumption model, including:
- structured reporting through Power BI
- self-service via DaaS-enabled semantic layers
- advanced analysis via notebook-based environments
- Provide ongoing visibility into delivery status, including day-to-day progress, risks, and blockers, ensuring stakeholders remain informed and aligned throughout execution
4.Governance & Compliance
- Develop and enforce enterprise data management standards, governance practices, and delivery guardrails across data, reporting, and related integrations
- Establish data governance, stewardship, and data quality practices that improve trust in reporting outputs across Finance, Actuarial, Underwriting, and Operations
- Design and implement a robust data security and access model across Microsoft Fabric, Power BI, and related platforms, including role-based access, data segmentation, and appropriate controls for sensitive data
- Ensure the data platform supports secure and governed self-service (DaaS), balancing accessibility for business users with control, consistency, and data protection
- Define and enforce standards for data access, consumption, and sharing, including internal usage (Power BI, notebooks, applications) and external data distribution (feeds, reporting, partners)
- Ensure data platform and reporting practices support auditability, traceability, and regulatory requirements, particularly in the context of external reporting and partner data exchange
QUALIFICATION STANDARDS
Educational Attainment:
- Bachelor's degree in Computer Science, Information Systems, or a related field or equivalent hands-on experience.
Professional Experience & Leadership
- 7 years of hands-on experience in data engineering, with at least 2 years in a leadership role.
- Proven experience leading, building, and mentoring data teams in a small to mid-sized organization.
- Extensive experience overseeing data warehouse projects from inception to completion.
Technical Skills
- Experience with Microsoft Azure data services is required.
- Strong SQL and Python skills; experience with Power BI and Medallion Lakehouse architecture is a plus.
- Deep understanding of data warehouse schemas (fact/dimension tables), ETL pipelines, and data modeling.
- Strong knowledge of data architecture, ETL processes, and data governance.
- Familiarity with Microsoft Fabric and Databricks platforms is highly desirable.
- Experience in the Commercial Insurance P&C domain is a must.
- Excellent communication, leadership, and project management skills.
- Demonstrated success managing diverse teams (onshore/offshore, consultants, FTEs).
Preferred Skills:
- Experience supporting pricing, actuarial, underwriting, and financial reporting use cases within a Commercial P&C environment
- Proven experience modernizing legacy reporting and data processes, including replacing or re-platforming vendor-managed or manual reporting solutions into enterprise data platforms
- Experience identifying and resolving data quality issues, inconsistencies, and gaps in legacy data processes, improving trust in reporting outputs
- Demonstrated ability to balance evolving business requirements with structured data design, avoiding both over-engineered solutions and ad hoc rework
- Experience designing and implementing governed self-service data models and semantic layers, enabling business-facing analytics and reporting (e.g., Power BI and DaaS models)
- Familiarity with external reporting and data exchange patterns, including structured ingestion and delivery of data feeds for partners, carriers, and regulatory requirements
- Experience designing and extending modern data platforms (e.g., Microsoft Fabric) beyond traditional medallion layers, including semantic model development, data governance (e.g., Purview), and structuring data to enable downstream analytics, applications, and AI use cases
