Policy Data Product Owner

Bridge Specialty Group•Daytona Beach, FL

5d•$140,000 - $160,000

About The Position

Brown & Brown is seeking a Policy Data Product Owner to define, prioritize, and enable trusted enterprise policy, coverage, placement, premium, carrier, intermediary, renewal, and servicing data products in the gold layer of its medallion architecture. The role translates stakeholder needs into a product vision, roadmap, prioritized backlog, acceptance criteria, quality standards, and adoption plan that support policy lifecycle intelligence, placement insights, retention analytics, carrier optimization, portfolio management, and self-service analytics. The Product Owner partners with placement leadership, policy administration stakeholders, producers, account executives and managers, carrier strategy, finance, operations, platform engineering, BI development, data governance, and downstream consumers. The role is accountable for product outcomes, including ensuring Policy-domain data products are valuable, usable, accurate, documented, secure, scalable, and aligned with enterprise data standards. It owns strategy, roadmap, backlog, stakeholder alignment, adoption, and value realization for capabilities involving policy detail and transactions, coverage, premium, revenue, carrier, intermediary, placement, renewal, retention, insured, producer, office, line of business, and reference data. The position is based in Daytona Beach, Florida. The stated annual pay range is $140,000–$160,000. Brown & Brown describes benefits including medical/Rx, dental, vision, life and disability insurance; an employee stock purchase plan, 401(k), student loan assistance and tuition reimbursement; mental health and advocacy services; paid time off, holidays, and preferred partner discounts. Eligibility and offerings may vary.

Requirements

At least 3 years of experience in data product ownership, product management, analytics product management, data analytics, policy administration analytics, placement analytics, insurance operations analytics, revenue analytics, or a related role; senior roles may require 5 or more years.
Experience managing a product roadmap, prioritized backlog, user stories, acceptance criteria, release planning, stakeholder communications, and adoption for data, analytics, or business intelligence products.
Strong understanding of analytical data platforms, SQL concepts, data modeling, data quality, reporting architecture, and the data product lifecycle.
Experience owning or enabling reporting datasets, analytical data structures, business-facing data products, dashboards, scorecards, or self-service analytics capabilities.
Experience with Policy-domain concepts, including policy details and transactions, coverage, effective and expiration dates, renewals, endorsements, cancellations, premium, revenue, commission, fees, carrier hierarchy, intermediary relationships, lines of business, product hierarchy, insured and client identifiers, producer attribution, office and profit center mapping, and lifecycle reporting.
Understanding of data quality, documentation, testing, reconciliation, and requirements validation practices.
Ability to clarify stakeholder needs, make prioritization decisions, validate outcomes, explain tradeoffs, drive adoption, and ensure analytical products deliver measurable business value.
Strong problem-solving and decision-making skills, including investigating data issues, assessing business impact, coordinating remediation, and balancing short-term needs with long-term scalability.
Clear communication skills and ability to explain product direction, metric logic, roadmap priorities, release decisions, data limitations, and analytical findings to technical and non-technical audiences.

Nice To Haves

Bachelor’s degree in data science, computer science, engineering, information systems, analytics, statistics, business, or a related field.
Experience with AMS360, Epic, RiskMatch, BenefitPoint, BAM, Nova, policy administration systems, carrier and intermediary data, policy performance dashboards, placement insights, carrier scorecards, renewal reporting, or related insurance data products.
Experience with Microsoft Fabric, Azure, Databricks, Snowflake, Denodo, SQL-based platforms, or similar data engineering and analytics technologies.
Experience with data pipelines, data marts, transformation logic, medallion architecture patterns, data quality checks, or reporting-ready data structures.
Familiarity with DevOps, DataOps, version control, automated testing, deployment pipelines, and release management for data assets.
Familiarity with Agile, Scrum, Kanban, product discovery, delivery management, OKRs, value measurement, stakeholder governance, and product adoption practices.
Experience in insurance brokerage, policy administration, placement, carrier strategy, revenue operations, financial services, retail, or other enterprise-scale matrixed organizations.
Familiarity with placement strategy, preferred carrier utilization, wholesale versus direct placement, carrier concentration, renewal management, policy lifecycle analytics, coverage gap identification, retention analytics, carrier scorecards, and adoption support for policy- and placement-facing tools.
Hands-on technical depth is valuable, though the role is accountable for product outcomes rather than day-to-day engineering execution.

Responsibilities

Define and maintain the Policy data product vision, strategy, roadmap, outcomes, release priorities, and value measures with business and technical stakeholders.
Own and prioritize the backlog for Policy-domain datasets and insight products, integrating policy, transaction, coverage, premium, revenue, insured, producer, office, carrier, intermediary, line-of-business, and reference data across source platforms.
Translate business problems and reporting requirements into product features, user stories, acceptance criteria, standard metric definitions, release plans, and enablement materials.
Define and steward Policy-domain metrics and analytical capabilities, including policy counts, premium, revenue, commission, fees, policy lifecycle events, carrier and intermediary measures, placement, renewals, retention, and portfolio movement.
Partner with upstream bronze- and silver-layer engineering teams to define source requirements, transformations, data quality expectations, business definitions, service-level needs, reconciliation methods, and dependencies.
Prioritize enhancement requests, defects, technical debt, data quality issues, adoption needs, source-system gaps, and stakeholder escalations according to business value, risk, feasibility, urgency, regulatory sensitivity, and product outcomes.
Lead data validation and product acceptance, including policy count reconciliation, premium and revenue tie-outs, lifecycle logic review, mapping validation, metric review, stakeholder signoff, defect triage, root-cause investigation, and release readiness decisions.
Coordinate remediation of Policy-domain data quality issues involving identifiers, policy numbers, coverage attributes, dates, line-of-business and product mappings, carrier and intermediary hierarchies, profit centers, naming conventions, and reporting discrepancies.
Create and maintain product documentation, including business requirements, user stories, metric definitions, lineage summaries, decision logs, release notes, known limitations, adoption materials, and signoff records.
Partner with BI, analytics, engineering, placement, finance, operations, and business teams to align dashboards, reports, analytical views, APIs, semantic models, and consumption experiences with standard definitions, user needs, priorities, access controls, and decision workflows.
Own adoption and continuous improvement for policy and placement products such as Policy Performance and Placement Insights dashboards, Carrier Scorecards, Digital Bluebook policy views, agent recommendations, RevTrax inputs, renewal intelligence, retention analytics, and coverage gap analysis.
Lead release readiness, launch communications, stakeholder enablement, adoption tracking, data-quality feedback loops, and post-release improvement planning.
Ensure Policy-domain data products meet enterprise requirements for data quality, security, traceability, privacy, access control, governance, retention, documentation, responsible use, and appropriate handling of policy, client, carrier, financial, and operational data.
Communicate product status, roadmap progress, risks, adoption results, metric changes, source limitations, quality findings, release impacts, and value realization to stakeholders and leadership.
Support reliable, role-appropriate insight into policy lifecycle activity, premium, revenue, renewals, retention, carrier concentration, intermediary usage, and portfolio movement, while reducing manual spreadsheet dependency and duplicated reporting.