Position Title : IT Director, Enterprise DataDepartment : NIP Group
REPORTING RELATIONSHIPS
Reports To: Roseanne Laudisio
Supervises: N/A
Interfaces With: N/A
DETAILS OF DUTIES AND RESPONSIBILITIES
ABOUT THE ROLE
We are seeking an experienced IT Director, Enterprise Data to lead the strategy, architecture, delivery, and governance of our enterprise data function. This role is accountable for ensuring that data initiatives translate into measurable business outcomes, with clear ownership of scope, priorities, deliverables, and alignment to business needs.
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, scalable, 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 to ensure clear alignment across upstream systems, downstream data platforms, and AI-driven use cases.
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.
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
Establish and enforce a disciplined intake, prioritization, and backlog management process, ensuring focus on the highest-value work and preventing misaligned or overbuilt solutions
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
Partner closely with the Director of Applications, Integrations, and AI Enablement to ensure coordination across upstream systems, integrations, and downstream data platforms
Enable business users to effectively consume and leverage data through structured self-service models, reducing reliance on ad hoc data requests and rework
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
Ensure enterprise data assets are accessible and usable by downstream applications, integrations, and AI capabilities, working closely with the leader responsible for applications, integrations, and AI enablement to operationalize data for application and AI-driven use cases
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
Establish disciplined intake, design review, and prioritization practices so work begins only when intended outcomes, business ownership, and architectural fit are clearly defined
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
Lead stabilization and recovery of critical initiatives when delivery perception or performance is at risk, introducing structure, clarity, and execution discipline
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
Act as a bridge between business and technical teams, ensuring that data solutions reflect both business intent and sound technical design
Provide ongoing visibility into delivery status, including day-to-day progress, risks, and blockers, ensuring stakeholders remain informed and aligned throughout execution
Partner closely with the CIO to align on strategy, timelines, priorities, and key deliverables, ensuring execution remains aligned to enterprise objectives
Proactively identify opportunities to improve or streamline reporting, data access, and decision-making processes based on observed business needs and platform capabilities
Communicate delivery progress, trade-offs, and outcomes clearly to stakeholders and leadership, including visibility into business value, efficiency gains, and data quality improvements
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
Drive adoption of governance practices in a way that supports both scalability and business usability, avoiding unnecessary friction while maintaining control
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).
Strong analytical and problem-solving skills. Critical thinking and problem-solving is a must.
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 replatforming 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
Experience enabling or supporting AI and advanced analytics workflows, including preparing and structuring governed data for consumption by applications, integrations, and AI-driven use cases
