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.
Responsibilities:
- 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.
