Sr. Revenue Data Analyst
Listed on 2026-10-18
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IT/Tech
Data Analyst, Data Engineering, Data Science Manager, Data Scientist
Job Description The Senior Revenue Data Analyst leads projects that leverage advanced data science skills to develop scalable tools, analyses, and reporting that improve Revenue Management performance. As an expert in Python and SQL, the role uses PySpark, Databricks, Tableau, and other analytics tools to tackle complex problems involving large sets of structured and unstructured data, transforming them into actionable insights and reliable solutions that improve business decision-making.
Job Description The Senior Revenue Data Analyst leads projects that leverage advanced data science skills to develop scalable tools, analyses, and reporting that improve Revenue Management performance. As an expert in Python and SQL, the role uses PySpark, Databricks, Tableau, and other analytics tools to tackle complex problems involving large sets of structured and unstructured data, transforming them into actionable insights and reliable solutions that improve business decision-making.
Note:
this role will be required to work from our Estero, FL office at least 4 days per week.
The starting salary for this role is $75,000, commensurate with experience.
- Market management reporting:
Analyze data and build reports in Tableau to provide visibility into key metrics and optimize revenue for the North America RAC division. - Leadership reporting:
Perform KPI evaluation, statistical testing, root-cause analysis, and forecasting to answer key Revenue Management leadership questions and present data-driven solutions clearly and strategically. - Data maintenance and source ownership:
Lead data-focused projects by designing, mapping, monitoring, maintaining, and troubleshooting Databricks data pipelines and sources that support reporting, ensuring data accuracy, reliability, and minimal downtime. - Automation:
Transform manual processes into automated processes or applications that prioritize efficiency and accuracy, giving business users more time to spend on revenue-accretive functions. Examples include alerts, algorithmic bid processing, automated data archiving, application design for user input, and automated data entry using virtual machines or bots through tools such as Python, PySpark, Databricks Apps, and Power Automate. - Collaborate and communicate across teams:
Work closely with internal and external teams to test, relay feedback, and ensure alignment with desired business outcomes. - Data storytelling:
Summarize and clearly communicate projects to stakeholders by explaining the business problem, presenting findings, designing a solution, and sharing the measured revenue impact. - Continuous improvement:
Build technical, functional, and professional expertise through ongoing development opportunities and emerging analytics practices. Identify and implement improvements that increase individual and team effectiveness. Mentor and develop data analysts by sharing best practices, providing guidance, and expanding the team’s overall capabilities and bench strength.
- Bachelor’s degree or equivalent required; preferably in statistics, data science, business analytics, machine learning, computer science, mathematics or another analytical field
- Minimum of 2 years previous experience in data or business analytics or 1 year experience and a master’s degree in the relevant subject matter required
- Technical skills required: SQL, Python
- Technical skills preferred:
PySpark, Databricks, Tableau - Useful technical skills for the role: R, machine learning, forecasting, other data visualization tools
- Proficient in critical thinking, problem solving and adaptability
- Expertise in collaborating with stakeholders to support, develop, and enhance reporting and tools
- An effective data storyteller who explains…
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