Description

Lead Analytics Engineer - Cloud Success Insights

The Cloud Success Insights team powers decisions and applications across Salesforce supporting teams in, Customer Support, Digital Success, Training, Certifications, Success Guides and Architects teams, we are making a significant strides in becoming a truly Data-Driven Enterprise — one built on trusted, governed golden data assets, world-class self-serve capabilities, and AI-ready data infrastructure

Our Team owns the vision, strategy, and execution of our internal data and insights product portfolio, with focus on Customer Success. This team partners deeply with Data Pipeline, Platform Engineering, Data Architecture, and Data Governance teams to deliver the data products that our customer success teams rely on every day to drive product adoption, customer satisfaction and reduce attrition. Our products span data pipelines, canonical datasets, dashboards, APIs, ML models, and self-serve frameworks that power analytics, AI, and product decision-making at scale

The data product leaders in the team bring both strategic vision and operational depth — someone to engage credibly with C-suite stakeholders, inspire a high-performing team, and drive a complex, multi-workstream enterprise initiative from vision to measurable impact.

Roles and Responsibilities

• 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, breaking down siloes and cultivating a common language across metrics for our product portfolio
• 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.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, AI, Information Technology, or related fields.
• 10+ years of proven experience as a
  • Data Analytics and BI Engineer
  • Product manager

Technical Expertise

• 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." You need to know if a spike in a no. is a genuine trend or just statistical noise.
• Strong problem-solving skills and the ability to think strategically about emerging technologies.

The "Modern" Analyst Skill (AI Literacy)

Our modern analyst knows how to use AI as a force multiplier:

• Augmented Analytics: Using AI tools - Claude Code, Gemini, etc.. - to automate repetitive cleaning tasks or to spot anomalies in massive datasets that a human might miss.
• Prompt Engineering for Data: Using LLMs to help write complex SQL queries or debug Python scripts and create self serve tools that create a WOW factor for our stakeholder teams

Leadership skills

• Exceptional communication and executive presence, with the ability to translate complex technical strategies into compelling narratives for C-suite audiences
• Proven ability to define and execute a vision for trusted, governed data assets and scalable self-serve data capabilities
• Experience building and scaling self-serve analytics and data enablement programs
• Experience partnering with and influencing partner organizations across the company at the leadership level
• Ability to operate effectively in fast-paced, ambiguous environments, balancing long-term strategic thinking with near-term execution