Key skills
PythonSQLTableauAIMLAgenticData EngineeringAnalyticsBISnowflakeGitVersion ControlSalesforceAgileCI/CDLeadershipChange ManagementRemote WorkCustomer Success
About this role
Role Overview
- Champion the development of canonical, single-source-of-truth golden data assets that serve Customer Success teams across, Customer Support, Digital Success, Training, Certifications, Success Guides and Architects.
- Build self-serve data capabilities that empower users to access, explore, and act on trusted data with minimal friction
- Partner with leadership across the company to identify and prioritize the highest-value opportunities where data products can improve decision-making, automate workflows, and accelerate growth
- Work across Data Engineering, Architecture, Platform, and Governance teams within IT as well as our key partners in Analytics & Data Science to ensure data products are scalable, reliable, and aligned with enterprise data standards
- Own the target-setting process and success metrics for the CS portfolio, using data to demonstrate impact, ROI and continuously raise the bar
- Establish and evolve product development practices across the team, including roadmap planning, backlog management, agile delivery, and cross-functional coordination
- Influence external product roadmap with best internal practices through effective storytelling, clear documentation, enablement programs, and change management
- Data Instrumentation & Strategy: Defining what data needs to be collected to measure product success.
- Data Governance & Ethics: Managing data privacy (GDPR/CCPA) and ensuring the ethical use of AI/ML models.
- Defining "North Star" Metrics: Moving beyond vanity metrics to find the data points that actually correlate with long-term growth.
Requirements
- Bachelor’s or Master’s degree in Computer Science, AI, Information Technology, or related fields.
- 5-8 years of proven experience as a Data Analytics and BI Engineer Product manager
- Strong knowledge of Advanced SQL, Statistical Literacy, and agentic AI skills development.
- Familiarity with the Salesforce ecosystem
- Proficiency with SQL(Snowflake), Python, Tableau and other BI tools
- Skilled in version control (Git) and CI/CD pipelines for production deployment.
- Analytical Skills Ability to translate complex AI and Data research into actionable engineering solutions.
- Proficiency in finding insights and building predictive tools and visualizations for story-telling
- Understanding probability distributions, hypothesis testing, and "p-values."
- Strong problem-solving skills and the ability to think strategically about emerging technologies.
Tech Stack
- Python
- SQL
- Tableau
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options