Senior Business Intelligence Analyst

Cambium Learning Group

1d•Remote

About The Position

Lexia's data is central to how we grow and how we demonstrate impact. We are seeking a Senior Business Intelligence Analyst to turn that data into timely, actionable reporting and analysis that shape outcomes across our go-to-market teams. Reporting to the Director of Data Strategy & Analytics, the Senior Business Intelligence Analyst will be a hands-on analytics partner to Customer Success, Marketing, and Sales. Working with the data models built by our Analytics Engineering team, you will develop the dashboards, KPIs, analyses and AI agents that help these teams understand performance, spot opportunities, and act on them. This role sits at the intersection of the business and our data. You will translate stakeholder questions into clear analytical approaches, communicate what the data shows and what to do about it, and help build the self-service and AI-enabled tools that let more of Lexia get answers directly.

Requirements

Bachelor's degree in business, economics, statistics, data science, analytics, or a related field.
5+ years of experience in an analytical role, with a preference for experience supporting sales, marketing, customer success, or business operations.
Advanced proficiency in Tableau (or a comparable BI tool) and exceptional SQL skills for querying and validating data in a cloud data warehouse (e.g., Redshift).
Experience working with curated data models built by data or analytics engineering teams; familiarity with Dbt is a plus.
Proficiency with Salesforce or another CRM, and with Excel.
Demonstrated experience producing business-driven dashboards and reports and developing meaningful KPIs.
Experience with go-to-market analyses such as campaign attribution, account scoring, pipeline analysis, or retention/churn analysis; familiarity with Python or R for statistical analysis is a plus.
Interest in or experience with AI-assisted analytics tools, such as AI agents, natural language query interfaces, or LLM-driven analytics.
Experience within a SaaS B2B or B2G organization preferred.
Curiosity and a passion for asking “why?” to get to the root of an issue, paired with effective deductive and problem-solving skills.
Excellent communication and data storytelling skills, with the ability to explain findings clearly to non-technical audiences.
Excellent attention to detail, excellent follow-through, and the ability to manage multiple priorities in a fast-paced, changing environment.

Nice To Haves

Familiarity with Dbt is a plus.
Familiarity with Python or R for statistical analysis is a plus.
Experience within a SaaS B2B or B2G organization preferred.

Responsibilities

Build, maintain, and continuously improve Tableau dashboards and reports that give Customer Success, Marketing, and Sales executives clear visibility into pipeline, bookings, renewals, product usage, campaign performance, and other key business metrics.
Develop and maintain meaningful, well-defined KPIs, ensuring metrics are consistent across reports and aligned with agreed-upon business definitions.
Deliver recurring business performance reporting and forecasting that executives can rely on for planning and operational conclusions.
Conduct in-depth analyses of revenue, customer, and operational data to answer key business questions, such as campaign attribution, account scoring, pipeline health, and retention/churn drivers.
Go beyond reporting what happened to explain why, and turn findings into clear, actionable recommendations through strong data storytelling.
Handle ad hoc and confidential analysis requests with accuracy, sound judgment, and appropriate care for sensitive data.
Use the data warehouse marts and Tableau Cloud data sources provided by Analytics Engineering as the foundation for reporting and analysis, writing SQL to explore, validate, and combine data as needed.
Translate stakeholder needs into clear data requirements and metric definitions, and partner with Analytics Engineering to request new or enhanced data models when gaps arise.
Identify and escalate data quality issues, and help establish consistent data and reporting standards that increase confidence in our numbers.
Serve as a day-to-day analytics partner to Customer Success, Marketing, and Sales, building proven working relationships and a deep understanding of each team's goals, processes, and data.
Scope requests with stakeholders, set clear expectations on timelines, and help prioritize work in partnership with the Director of Data Strategy & Analytics.
Contribute to the design and rollout of self-service dashboards, AI agents, and conversational analytics tools that enable non-technical staff to answer questions of our data directly.
Support stakeholder enablement through documentation, training, and office hours, and follow data and AI governance policies to ensure analytics tools and data are used appropriately.
Look for opportunities to automate recurring work and apply new tools and best practices that improve scale, efficiency, and quality.