Sales Data Product Owner

Brown & Brown Insurance•Daytona Beach, FL

2d•$140,000 - $160,000

About The Position

Brown & Brown is seeking a Sales Data Product Owner to define, prioritize, and enable trusted enterprise data and insight products in the gold layer of its medallion architecture, with a focus on the Sales domain. The role translates sales leadership, producer, CRM, pipeline, revenue, cross-sell, account-rounding, and forecasting needs into a product vision, roadmap, prioritized backlog, acceptance criteria, and adoption plan. These products support executive reporting, operational sales insights, producer performance management, and self-service analytics. The position works closely with sales leadership, Sales Operations, producers, account teams, platform engineering, BI development, data governance, and downstream consumers. It ensures Sales-domain data products are valuable, usable, accurate, documented, scalable, and aligned with enterprise data standards. The role owns product strategy, stakeholder alignment, adoption, and value realization for products involving CRM, pipeline, opportunities, producer performance, revenue, sales goals, cross-sell, account rounding, and forecasting.

Requirements

At least 3 years of experience in data product ownership, product management, analytics product management, data analytics, sales operations analytics, CRM 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 activities 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 Sales-domain concepts such as opportunities, pipeline stages, closed-won revenue, producer performance, sales goals, first appointments, hit ratio, cross-sell, account rounding, CRM activity, book-of-business segmentation, and sales leader 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 the ability to investigate data issues, assess business impact, coordinate remediation, and balance immediate stakeholder needs with long-term product 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 Salesforce, Microsoft Dynamics, CRM data models, sales dashboards, producer scorecards, CRM adoption metrics, or related sales enablement reporting.
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, sales operations, revenue operations, financial services, retail, or other enterprise-scale matrixed organizations where sales data, producer performance, customer growth, retention, and pipeline management are core priorities.
Familiarity with sales incentive programs, cross-sell and account-rounding analytics, producer business planning, opportunity management, CRM data quality, and adoption support for sales-facing analytical tools.
Hands-on technical depth with data platforms and analytics technologies.

Responsibilities

Define and maintain the Sales data product vision, strategy, roadmap, outcomes, release priorities, and value measures with sales leadership, Sales Operations, data engineering, BI, governance, and business stakeholders.
Own the prioritized backlog for Sales-domain datasets and insight products integrating CRM activity, opportunities, producer hierarchy, book-of-business attributes, sales goals, revenue results, and reference data across platforms such as Salesforce and Microsoft Dynamics.
Translate business problems, stakeholder needs, and reporting requirements into product features, user stories, acceptance criteria, standard metric definitions, release plans, and enablement materials.
Define and steward Sales-domain metrics and analytical capabilities for closed-won revenue, open pipeline, first appointments, hit ratio, pipeline per producer, producer scorecards, sales attainment, CRM adoption, and sales leader dashboards.
Partner with upstream bronze- and silver-layer engineering teams to define source requirements, transformation rules, data quality expectations, service-level needs, and delivery dependencies.
Prioritize enhancement requests, defects, technical debt, adoption needs, and stakeholder escalations according to business value, risk, feasibility, urgency, and alignment with Sales-domain outcomes.
Lead data validation and product acceptance, coordinating reconciliation, metric review, stakeholder signoff, defect triage, root-cause investigation, and release-readiness decisions.
Coordinate resolution of Sales-domain data quality issues, including inconsistent producer mappings, CRM source alignment, missing opportunity records, stale reference data, spreadsheet dependencies, and reporting discrepancies.
Create and maintain product documentation, including requirements, user stories, metric definitions, data lineage summaries, decision logs, release notes, known limitations, adoption materials, and stakeholder signoff records.
Partner with BI, analytics, engineering, and business teams to align dashboards, reports, analytical views, and consumption experiences with standard definitions, user needs, product priorities, and Sales-domain decision workflows.
Own adoption and continuous improvement for sales enablement products such as Sales Insights dashboards, producer scorecards, Get Sales Done reporting, Pedal to the Metal reporting, Digital Bluebook sales views, and future sales-agent recommendations delivered through Teams, email, CRM, or other enterprise channels.
Lead release readiness, launch communications, stakeholder enablement, adoption tracking, and post-release feedback loops for Sales-domain data and analytical products.
Ensure Sales-domain data products comply with enterprise standards for data quality, security, traceability, privacy, access control, governance, documentation, and responsible use.
Communicate product status, roadmap progress, delivery risks, adoption results, metric changes, data limitations, and value realization to stakeholders and leadership.