• Review (AW) dashboard design guidelines with the AW Power BI Lead to ensure consistent UI/UX across screens. • Build the Power BI semantic/reporting layer, including model relationships, measures, and report logic • Develop three dashboard screens aligned to approved wireframes and business priorities • Implement KPI measures/calculations in DAX, validating results against approved KPI logic and curated Databricks consumption-layer datasets • Configure interactivity: filters, slicers, drill behavior, cross-visual interactions, and navigation patterns • Apply report formatting and usability enhancements to deliver a polished executive dashboard experience • Support performance tuning (query efficiency, model/report optimization, and visual responsiveness) • Participate in iterative demos, incorporate feedback, and resolve defects during testing cycles (QA/UAT) • Support deployment readiness activities as needed

• Develop and manage effective working relationships with other departments, groups and personnel with whom work must be coordinated or interfaced • Gather and document functional and technical requirements, and translate requirements into reporting solutions, analytic tools and dashboards • Develop in-depth understanding of underlying data, data structures, and business uses to ensure reports meet client needs • Create simple to complex data solutions by leveraging database design, performance tuning, query optimization, indexes, data migration tools, and data analysis of back end data generated by FLVS products and services • Coordinate quality control and peer review processes to ensure integrity of the data available to users • Review queries for performance issues, making changes as needed • Create technical documentation of report logic and processes • Work with Developers to understand code changes that will impact analytics and tools • Support end-user community in the use of business intelligence tools to query databases and files for report outputs • Develop key operational, financial and customer centric dashboards and metrics • Develop and assist with training through the development of training tools and training of key staff • Provide support as required to ensure the availability and optimized performance of developed reports and dashboards for both external and internal users • Design and implement technology best practices, guidelines and repeatable processes • Work with Production team to ensure new reports and/or processes abide to Production development standards • Provide a minimum of weekly status report updates for current projects • Meet professional obligations through efficient work habits such as, meeting deadlines, honoring schedules, coordinating resources and meetings in an effective and timely manner, and demonstrate respect for others

• Develop metrics and dashboards with business stakeholders to track business key performance indicators • Collaborate with data engineering to support and validate data architecture • Provide user assistance and direction for ad-hoc data reporting • Collaborate with key stakeholders to build new analytic processes and improve current processes

• Partner with Sales stakeholders to define analytical requirements, metrics, and KPIs, and identify opportunities for improvement. • Develop and maintain dashboards, reports, and visualizations that provide timely and actionable insights. • Analyze revenue streams and contribute to forecasting using statistical, heuristic, or machine learning approaches. • Perform exploratory and ad hoc analyses to support decision-making across Sales and related teams. • Collaborate with data engineers to design and implement data marts, reporting layers, and ETL pipelines; contribute to our dbt-based analytics infrastructure. • Support Sales Development and Lead Generation teams by analyzing experiments and campaign performance. • Monitor data quality across reporting assets and work with data owners to resolve issues. • Document metrics, dashboards, and data sources, and help stakeholders effectively use analytics tools. • Promote self-service analytics by enabling teams to access and interpret data independently.