Senior Data Analyst, Sales Analytics
- Lead the full-cycle Sales analytics function, including requirements gathering, large-scale data analysis, KPI development, and the design and delivery of impactful dashboards and reports.
- Design, develop, and maintain critical Sales performance dashboards and KPIs, with a focus on usability, scalability, and data integrity.
- Leverage Apache Airflow for managing data pipelines, and use API integrations to enrich data sources, automate data workflows, and expand reporting capabilities.
- Own and enforce data quality standards by implementing rigorous data validation, transformation logic, and anomaly detection practices.
- Conduct detailed data investigations to uncover trends, surface root causes, and develop actionable business insights.
- Translate complex analytics into clear, compelling narratives through data storytelling, visualizations, and presentations tailored to business and executive stakeholders.
- Drive efficient data extraction and transformation strategies across multiple sources (cloud and on-prem), collaborating with Data Engineering to maintain high-scale, performant data infrastructure.
- Act as a global analytics lead, aligning priorities across regional teams, Tableau platform owners, and Data Engineering, ensuring consistency and scalability of analytics assets.
- Partner with Engineering to enhance the Sales data mart and enterprise data warehouse, including development of new data models and enrichment layers.
- Contribute to the design and optimization of ETL pipelines, identifying opportunities for automation, improved performance, and increased reliability.
- Collaborate closely with Finance and Revenue teams to perform monthly revenue reconciliations, ensuring consistency between operational metrics and financial reporting.
- Manage Tableau environment responsibilities, including permissions management, user access provisioning, dashboard governance, and coordination with Tableau Admins.
- Build strong cross-functional partnerships with Sales, Marketing, Customer Success, Delivery, Service, Finance, Legal, and Data Engineering, acting as the analytics thought partner across the business.
- Proactively manage change in a dynamic environment by partnering closely with Product Owners and Program Managers to understand shifting business processes or systems, ensuring analytics solutions adapt smoothly without disrupting decision-making or operational continuity.
- 5+ years of experience in Data Analytics, Business Intelligence, or Data Science roles, with a focus on Sales analytics or Finance Analytics.
- BS/MS in a quantitative discipline: Analytics, Computer Science, Statistics, Engineering, Mathematics, or a related field.
- Expert-level SQL skills, with demonstrated ability to manipulate, join, and analyze complex, large-scale datasets.
- Familiarity in Python or R for data analysis, statistical modeling, and automation.
- Fluency in Tableau, including advanced dashboard development, permission/access control, with close collaboration experience with Tableau Server Admin teams.
- Proficiency in data visualization best practices, creating intuitive and actionable dashboards for a wide range of stakeholders.
- Strong hands-on experience with Apache Airflow, especially in orchestrating workflows and managing ETL jobs.
- Experience with API integration for data extraction, enrichment, and automation use cases.
- Deep understanding of Salesforce (SFDC) data models and their use in tracking the full customer lifecycle.
- Familiarity with data mining, data modeling, mapping, and integration across diverse data environments (cloud and on-prem).
- Proven experience conducting financial data reconciliation and partnering with Finance teams to align on definitions, metrics, and validation protocols.
- Excellent written and verbal communication skills, with the ability to distill complex data into compelling stories for both technical and non-technical audiences.
- Demonstrated success in agile environments, with experience using project management tools like JIRA.
- Demonstrated ability to manage through change by building strong, trusted relationships with Product, Program, and Engineering stakeholders, and adapting analytics solutions to evolving business and system landscapes.
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