Senior Business Analyst – Retail Data Products

Brown & Brown Insurance•Daytona Beach, FL

11d

About The Position

Brown & Brown is seeking a Senior Business Analyst – Retail Data Products to join its team in Atlanta, Georgia; Dallas, Texas; or Daytona Beach, Florida. The role supports the design, delivery, governance, and quality of enterprise data products and analytics solutions. It bridges business and technology by translating requirements into scalable data solutions while promoting high data quality, trusted KPIs, and governed self-service analytics. The analyst partners with Data Product Leads, Data Engineering, business stakeholders, and third-party partners to enable data-driven decision-making across the enterprise. The position contributes across requirements gathering and data product delivery, hands-on data analysis and validation, data quality and governance, testing and release execution, data platform and partner oversight, documentation and standards, change management, business enablement, and cross-functional collaboration. It also supports governed SDLC practices, regulatory and data-policy compliance, self-service analytics adoption, and clear communication of project status, risks, and insights.

Requirements

Bachelor’s degree in Analytics, Information Systems, Computer Science, or a related field.
5–8+ years of experience in business/data analysis, BI, or data product support roles.
Strong SQL and data analysis skills.
Experience with data platforms and data warehousing and modeling concepts.
Hands-on experience gathering requirements, supporting Agile delivery (including user stories and backlog management), and performing data validation and reconciliation.
Knowledge of data governance, lineage, metadata, data quality frameworks, and KPIs.
Strong communication and stakeholder management skills.

Nice To Haves

Experience with cloud platforms focused on Data, AI, and Analytics product outcomes.
Exposure to ETL/ELT tools and data catalog or governance tools.
Experience working with third-party data partners.
Industry experience in insurance, finance, or similar data-heavy environments.
Familiarity with MDM concepts, including customer master, deduplication, and 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 an ownership mindset.
Ability to influence cross-functional stakeholders without authority.

Responsibilities

Elicit, document, and prioritize data and analytics requirements with stakeholders.
Translate business needs into user stories, data definitions and mappings, and acceptance criteria.
Support the design and delivery of data pipelines, curated datasets, and data products.
Participate in Agile delivery processes, including backlog grooming, sprint planning, and prioritization, and represent customer needs to data teams.
Use SQL to analyze data, validate and reconcile information across systems, investigate root causes of data issues, and support ad hoc analysis and KPI validation.
Deliver analytics that support operational, financial, and strategic decision-making.
Own and enforce data quality standards and governance frameworks, including defining and monitoring data quality rules, KPIs, SLAs, and controls.
Maintain data dictionaries, KPI catalogs, business glossaries, and lineage documentation.
Lead data stewardship workflows, issue intake, triage and resolution, governance forums, and audits.
Ensure compliance with regulatory requirements and data policies.
Develop and execute test plans, UAT, regression testing, and data reconciliation processes.
Validate datasets, transformations, and reporting outputs before release; support release management and documentation; and ensure adherence to a governed SDLC.
Collaborate with data engineering teams and external partners to validate data models and transformations and ensure delivered data assets align with business requirements and governance standards.
Serve as a liaison between business, IT, and data partners.
Create and maintain documentation for data models, KPIs, transformations, and data contracts.
Establish and enforce naming conventions, certification standards, and technical documentation practices.
Drive adoption of self-service analytics and governed datasets, lead user training and enablement, and improve data literacy across functions.
Support change management initiatives and governance adoption.
Partner with data engineers, data scientists, enterprise finance, sales, operations, marketing, IT, and architecture teams.
Communicate project status, risks, and insights; lead meetings, resolve issues proactively, and drive alignment.