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Summary: The Senior Business Intelligence Analyst plays a pivotal role in driving data-driven decision-making across the organization. This role is responsible for developing dynamic dashboards, delivering actionable insights, and ensuring the effective use of analytics tools to support strategic objectives.
Develop, maintain, and enhance Amazon Quicksight dashboards and reports to provide visibility into key business metrics. Analyze GTM data to deliver insights that improve decision-making and drive business outcomes. Create robust data models to streamline reporting and ensure alignment with strategic objectives. Design, implement, and manage weekly, monthly, and quarterly scorecards and forecasts for leadership. Partner with Sales, Marketing, and Customer Experience teams to ensure reporting aligns with business needs. Lead the administration and enhancement of Quicksight and other BI platforms to ensure scalability and usability. Provide provocative presentations to key stakeholders to advance understanding and strategy through compelling visuals. Educate GTM teams on how to use BI tools effectively, fostering a data-driven culture. Develop standardized reports and packages that provide field teams with the insights they need to succeed. Respond to requests for deep-dive analyses to uncover trends, opportunities, or risks. Required Skills & Experience: 4+ years in Business Intelligence, Data Analytics, or a related field, with hands-on expertise in AWS Quicksight. Proficiency in SQL, Python, dbt, data modeling, data visualization, and advanced Excel/Google Sheets for modeling and analysis. Experience with AWS Quicksight/Athena/S3/Lambda, Gitlab, VSCode, Salesforce CRM, Google Sheets, Google Slides. Preferred experience with Fivetran. Strong ability to interpret data, identify trends, and translate findings into actionable strategies. Exceptional attention to detail and a knack for solving complex business problems. Ability to clearly convey insights and recommendations to both technical and non-technical stakeholders. Bachelor’s degree in Data Science, Computer Science, Analytics, or a relevant/equivalent field. Working knowledge of SaaS metrics (Bookings, Pipeline, Churn, NRR, GRR, LTV, ARR, CAC, etc.) and Revenue Forecasting. Bonus points for experience with other BI tools (e.g., Tableau, Power BI) and domain expertise in revenue enablement, GTM/sales operations, professional services reporting, customer intelligence, or churn prediction models.