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Intuit is a global technology platform that helps consumers and small businesses overcome their most important financial challenges. Serving more than 100 million customers worldwide, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Overview

The Customer Success (CS) Data and Analytics team has an exciting opportunity to improve customer experiences using data. We are seeking an exceptional Sr. Manager of Data to lead programs and enable world-class data and analytics capabilities to deliver better customer benefits and outcomes. This role will lead a high-performing team of Technical Data Analysts driving Customer Success data initiatives to enable the business to act quickly on data insights to inform better customer experiences and drive innovation.

You will draw upon solid analytical, critical thinking, and problem-solving skills to effectively manage your resources and successfully drive a portfolio of vital programs. You will quickly establish rapport, credibility, trust and respect throughout the organization at all levels, and be viewed as a team player. This leader partners closely with data engineering, product management, product development engineering, operations, and data analytics leaders across Intuit.

This is an exciting time to join Customer Success at Intuit as we are building a service platform to help our customers beyond core product use. This is your opportunity to join this exciting and transformational journey.

What you'll bring

• Proven leader in data space with 7-10 years of experience leading conversations across teams to drive for clear business requirements as well as build and launch products
• Strong people management skills leading teams for 3-5 years and growing data talent
• Understand large-scale data platform capabilities and possess enough technical depth in the areas across these data capabilities (analytics and engineering) to assess risk and find solutions
• Demonstrated ability to think end-to-end, lead long-term programs, and to manage multiple programs simultaneously within a program portfolio
• Demonstrates highly effective cross functional leadership and experience working in a large matrixed organization, aligning cross functional stakeholders, gathering business requirements, and delivering data solutions
• Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
• High level of professionalism, passion and a sense of urgency to "make things happen"
• Strong strategic-mindset, but also willing to roll up your sleeves and get into the details, coaching team members where needed

• Self-starter who seeks the problem, doesn't wait for the problem to find them with excellent problem-solving skills and end-to-end quantitative thinking
• Strong organization, time management and task prioritization skills with attention to detail and bias to action
• Ability to tell stories with data, educates effectively, and instills confidence in recommendations, motivating others to act on them

• Experience working with BI tools preferred such as Qlik, Tableau, PowerBI etc.
• Experience with instrumentation, clickstream data, and data architecture preferred
• Technical undergraduate degree (Engineering, Computer Science, Statistics, Analytics etc.) or equivalent experience
• Some travel required (~10%)

How you will lead

• Partner with product management/engineering, data engineering, and analytics teams to deliver standardized and consistent analytics data needed to drive AI-driven platforms

• Collaborate with stakeholders and analysts to ensure data solutions are scalable, repeatable, effective, and meet expectations of various stakeholders
• Create execution plans with tangible processes and frameworks to drive rigor and structure, and help teams adopt and repeat with high standards
• Drive collaboration with internal and external customers and partners (e.g. engineering, product/design, data analytics, data science, and vendors) to firm up data requirements and prioritize deliverables

• Pursue data quality, troubleshoot data validation, and see issues to resolution

• Continuously improve the operating framework that enables the data organization to achieve its goals
• Provide recommendations utilizing multiple types of data, business knowledge, and strategic assumptions when data does not exist

• Ensure data collection and processing is optimized to provide clear visibility into the impact and value of new initiatives and product releases

• Mitigate risk and solve problems through innovative ideas and solutions
• Be a leader/teacher who role models leadership and domain expertise