We’re looking for a Business Data Analyst to join our Revenue Operations Team to help drive sales and marketing performance improvements within the business. Not only will you have a strong technical skill-set, you’ll also have demonstrable stakeholder management, influencing and relationship building skills in order to help make recommendations and advise the business. We work in a fast-paced environment here at Sangoma, so you’ll also be highly organized and will have the ability to manage your time effectively. We’re seeking someone who is technically strong using business intelligence tools.
- Gather BI requirements from business teams.
- Build and deliver high quality analytical solutions using BI tools.
- Compile monthly/quarterly reports for analysis, forecasting and commissions.
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for internal staff.
- Present actionable insights and recommendations to business leaders to improve revenue performance.
- Become a trusted business partner to Sales and Go-To-Market leadership, and play a critical role scaling the company’s rapidly growing revenue operations organization.
- Bachelor's degree or higher in a quantitative/technical field (e.g. Business Analytics, Statistics, Engineering).
- 3+ years of relevant experience in one of the following areas: Business intelligence, data engineering, database engineering or business analytics.
- 2+ years of hands-on experience in writing complex SQL queries across large data sets.
- Knowledge of statistical and optimization modeling.
- Experience with using data visualization tools like Grafana, Tableau, Qlikview, Mode, etc
- Experience with salesforce
- Understanding of marketing and sales strategies
- Experience in working and delivering end-to-end projects independently.
- Previous practical experience within a data analyst role, preferably within a Sales, Marketing or Commercial setting
- Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.