Brown & Brown is seeking aSenior Business Analyst 6 Retail Data Productsto join our growing team in Atlanta, GA, Dallas, TX, or Daytona Beach, FL.

This role will support the design, delivery, governance, and quality of enterprise data products and analytics solutions. This role bridges business and technology, translating requirements into scalable data solutions while ensuring high data quality, trusted KPIs, and governed, self-service analytics. The analyst will partner closely with Data Product Leads, Data Engineering, business stakeholders, and third-party partners, playing a critical role in enabling data-driven decision-making across the enterprise.

How You Will Contribute:

Requirements & Data Product Delivery

Partner with stakeholders to elicit, document, and prioritize data and analytics requirements

Translate business needs into:

• User stories

• Data definitions and mappings

• Acceptance criteria

Support design and delivery of:

• Data pipelines

• Curated datasets

• Data products

Participate in Agile delivery processes (backlog grooming, sprint planning, prioritization)

Act as the voice of the customer for data teams

Data Analysis & Validation

Perform hands-on data analysis using SQL

Validate and reconcile data across systems

Conduct root-cause analysis for data issues and discrepancies

Support ad hoc analysis, KPI validation, and business insights

Deliver analytics for operational, financial, and strategic decision-making

Data Quality & Governance

Own and enforce data quality standards and governance frameworks

Define and monitor:

• Data quality rules and KPIs

• Data SLAs and controls

Maintain:

• Data dictionaries

• KPI catalog

• Business glossaries

• Lineage documentation

Lead governance processes include:

• Data stewardship workflows

• Issue intake, triage, and resolution

• Governance forums and audits

Ensure compliance with regulatory and data policies

Testing, Release & SDLC Execution

Develop and execute:

• Test plans

• UAT and regression testing

• Data reconciliation processes

Validate datasets, transformations, and reporting outputs before release

Support release management and documentation

Ensure adherence to a governed SDLC

Data Platform & Partner Oversight

Collaborate with data engineering teams and external partners

Validate data models and transformations

Ensure delivered data assets align with business requirements and governance standards

Act as liaison between business, IT, and data partners

Documentation & Standards

Create and maintain comprehensive documentation for:

• Data models

• KPIs

• Transformations

• Data contracts

Establish and enforce:

• Naming conventions

• Certification standards

• Technical documentation practice

Change Management & Business Enablement

Drive adoption of self-service analytics and governed datasets

Lead training and enablement sessions for business users

Improve data literacy across functions

Support change management initiatives and governance adoption

Cross-Functional Collaboration

Partner with:

• Data Engineers, Data Scientists, Enterprise

• Finance, Sales, Operations, Marketing

• IT and Architecture teams

Communicate project status, risks, and insights to stakeholders

Lead meetings, resolve issues proactively, and drive alignment

Skills & Experience to be Successful:

Required

Bachelor99s degree in Analytics, Information Systems, Computer Science, or related field

5 68+ years in business/data analysis, BI, or data product support roles

Strong SQL and data analysis skills

Experience with:

• Data platforms

• Data warehousing and modeling concepts

Hands-on experience with:

• Requirements gathering

• Agile delivery (user stories, backlog management)

• Data validation and reconciliation

Knowledge of:

• Data governance, lineage, metadata

• Data quality frameworks and KPIs

Strong communication and stakeholder management skills

Preferred

Experience with Cloud Platforms focusing on Data, AI & Analytics product outcomes

Exposure to:

• ETL/ELT tools

• Data catalog/governance tools

Experience working with third-party data partners

Industry experience (Insurance, Finance, or similar data-heavy environments)

Familiarity with MDM concepts (customer master, deduplication, golden records)

Exposure to AI/ML-ready data ecosystems

Strong analytical thinking and problem-solving

Ability to translate between business and technical teams

Attention to detail in data validation and governance

Self-directed execution and ownership mindset

Influence without authority across cross-functional stakeholders