Data Product Manager

Job Type:

Permanent

Build a brilliant future with Hiscox

Product Manager, Core Change & Steady State

Position: Data Product Manager

Reports To: Director of Product & Delivery, Data Organization

Location: Atlanta, GA; Boston, MA; NYC Manhattan; West Hartford, CT (Hybrid)

The Team:

Our Data organization creates and manages a portfolio of trusted, reusable, and governed data products that deliver measurable business value and drive profitable growth for the company. We operate an agile, product-based delivery model with cross-functional scrum teams aligned to business objectives and key results. We are in the midst of a deliberate shift toward an AI-first operating model — embedding AI, GenAI, and intelligent automation directly into how we discover, model, build, test, monitor, and support data products, so that every core and steady-state capability we own becomes faster to deliver, easier to trust, and cheaper to run over time.

About the Role:

We are looking for a Product Manager to own the core change and steady-state products that form the backbone of our Data organization — the foundational data platforms, conformed and curated data layers, business-as-usual (BAU) feeds, and the recurring enhancements that keep our data ecosystem reliable, governed, and ready for the next wave of AI-enabled use cases.

This is a hands-on, technically grounded product role for someone who has lived inside a Data organization: someone fluent in data frameworks and methodologies, comfortable navigating a modern data lakehouse and cloud data platform, and confident enough with SQL and data modeling to have real conversations with engineers about how conformed and curated data structures should evolve. You will balance the steady drumbeat of core changes and BAU support against the organization's push toward AI-first ways of working, ensuring that stability, governance, and continuous modernization move forward together rather than competing for attention.

You will own the roadmap, backlog, and outcomes for this product area, partnering closely with delivery leads, data engineering, analytics engineering, architecture, and business stakeholders across the US value chain (marketing, operations, underwriting, claims, distribution, and finance) to ensure our data products keep pace with evolving business needs.

What You'll Do:

Core Change & Steady-State Product Ownership

Own the product vision, roadmap, and backlog for core/foundational data platforms, conformed and curated data layers, BAU feeds, and recurring change requests.

Balance new demand (core change) against the health of steady-state operations — data quality, platform stability, and reduction of technical debt.

Continuously evaluate and evolve conformed and curated data models so they stay aligned to shifting business use cases, reporting needs, and downstream data product outcomes.

Champion the organization's move to an AI-first operating model by identifying opportunities to embed AI and automation into data discovery, modeling, quality monitoring, and support workflows for core and steady-state products.

Apply data frameworks and methodologies (e.g., medallion/bronze-silver-gold architecture, data mesh or domain-oriented principles, data governance and stewardship standards) to guide sound product and design decisions.

Own product intake, prioritization, success measures, and monitoring to ensure Data Products remain relevant, achieving business outcomes/value as well as defined performance and functional service levels.

Requirements & Stakeholder Management

Partner with business stakeholders and Data Delivery teams to translate business needs into clear user stories, functional/non-functional specifications, acceptance criteria, and prioritized backlog items.

Elicit, challenge, and document requirements for core changes, working with source system owners, data engineers, and architects to define source-to-target mappings, lineage, and data quality controls.

Perform hands-on data analysis and SQL-based investigation to validate data quality, troubleshoot issues, and inform data model and product decisions.

Manage data-related incidents, availability questions, and escalations for core platforms and BAU feeds, communicating clearly with technical and non-technical audiences alike.

Validate and sign off on new foundational data elements, confirming accuracy, functionality, and Enterprise Data management (EDM) standards are met.

Collaboration & Delivery Partnership

Partner with the Delivery Manager and Scrum Masters to keep core change and steady-state features refined, sequenced, and ready for delivery.

Work with data engineering and architecture teams to reduce technical debt, retire legacy patterns, and move business logic into the appropriate data layer.

Communicate roadmap, tradeoffs, dependencies, and progress toward AI-first adoption clearly to both technical teams and business/executive stakeholders.

Maintain strong working relationships across the organization, including Architecture, Governance, Platform Operations, and peer Product Managers.

What Success Looks Like:

Outcomes are defined to make goal-setting, Performance & Development Reviews (PDRs), and mid-year reviews straightforward:

Platform & Data Reliability — Core platforms and BAU feeds are stable, monitored, and consistently meet agreed data quality and availability standards.

Well-Aligned Data Models — Conformed and curated data models are proactively evolved to match current and emerging business use cases and data product outcomes.

Governed Layers — Clear, enforced separation of raw/silver/gold with metadata and lineage managed in Unity Catalog.

AI-First Progress — Measurable adoption of AI and automation within core change and steady-state workflows, in line with the organization's AI-first operating model.

Roadmap Health — A prioritized, transparent roadmap that balances new core change demand with the ongoing health of steady-state operations.

Stakeholder Trust — Strong, trust-based relationships with business stakeholders and engineering partners, evidenced by clear communication and reliable delivery.

Our Must Haves:

Minimum 5 years of experience as a Product Manager or Product Owner with a data platform, data engineering, or core data focus.

Property & Casualty (P&C) insurance industry experience.

Familiarity with data frameworks and methodologies, data warehousing concepts, governance, and data quality

Deep analytical skills and working knowledge of SQL and cloud data platforms, with the ability to independently query, investigate, and validate data.

Demonstrated ability to understand and evolve conformed and curated data models to best align them to business use cases and intended data product outcomes.

Experience defining platform or engineering-enablement roadmaps and translating technical needs into a prioritized backlog.

Strong verbal and written communication skills, with the ability to translate between technical and business audiences.

Experience working with cross-functional agile teams, facilitating consensus on scope, design, and prioritization decisions.

Our Nice to Haves:

Hands-on experience with cloud data and analytics platforms such as Databricks, BigQuery, or equivalent, and familiarity with data lineage and metadata management tools such as Unity Catalog or Dataplex.

Exposure to AI-first or AI-enabled data operating models, including use of AI/GenAI in the data product development lifecycle.

SAFe POPM, CSPO, or equivalent agile product management certification.

Experience with Objectives and Key Results (OKRs) and Organizational Change Management (OCM).

Experience working as part of a globally distributed team.

Hiscox Values:

At Hiscox our spirit is in Challenging Convention and everything we do is guided by our Values.

Courage: Dare to take a risk

Ownership: Passionate, commercial an