Intuit Staff Technical Data Analyst in Mountain View, California



Come join the Small Business Group at Intuit as a Staff Techincal Data Analyst, diving head first into one of our most critical projects supporting quickbooks.  Quickbooks exists to fuel small businesses by providing the toolset necessary to run their businesses, and we are working hard to make quickbooks better world-wide. 


Our Finance Data Analytics team in the Small Business Group is comprised of finance, analytics, and data-science professionals, leveraging our collective skills to tackle substantive challenges and drive smart decision-making.  We work across initiatives on projects spanning data infrastructure, financial modeling, data visualization, analysis, and distributed machine-learning to drive impact to our bottom line. 


We’re looking for a staff analyst to join our team, where you’ll be working hand in hand with product managers to drive the success of a re-platform of our billing system.  This is a dedicated year-long project, where you’ll become a deep expert on our systems, and will work closely collaborating between both technical and non-technical teams.  The ideal candidate is the type that in order to truly grok how a thing works will pull it apart, try to break it, and put it back together again.  Someone who can be rigorous when required, but knows when “done” is better than "perfect".



  • Own and drive data warehousing changes necessary through this re-platform.  Collaborate with product development and data engineering teams to ensure capture of the right data.  Prototype and provide guidance for data engineering, working together to ensure a smooth transition of business reporting and analysis capabilities from our old system to our new.

  • Own partnering with product management to be an expert on the data, provide the research, and build knowledge of the nuances necessary to help determine segmentation and timing strategies.

  • Own the reporting and monitoring of this project.  Ensure that the right monitoring is in place so that in the off chance something goes wrong, we catch it immediately, alarm bells are raised, and we can pinpoint and address the problem in near real-time.

  • Be the point of contact for deep-dive analytics questions, as well as diagnosing and problem-solving through fire-drills.

  • Provides guidance and support leadership to Business leaders and stakeholders on how best to harness available data, extract meaning, reconcile assumptions, and identify logical path for action.

  • Build deep subject matter expertise on our product and billing systems, able to voice the nuances of how customer experience translates from our data.

  • Build and socialize decision tools (dashboards, reports) and key data sets/pipelines to empower operational and exploratory analysis.

  • Applies proven methods and hacking skills in working with divergent data types and data scales, to explore and extrapolate data-driven insights.  Apply statistical modeling and testing to data acquired and cleansed from a range of sources (relational databases and non-relational data) to get to reliable insights and to empower rigorous and hypothesis-driven decision making.

  • Uses considerable expertise and independent judgment in collaborating with peers, product managers, developers, and data engineers, in designing and implementing the research strategy needed to methodically and iteratively structure, extract, cleanse, sample, test, validate, and communicate data-driven insights from complex sources and significant volumes of data.

  • Collaborates with business stakeholders in acting on complex, multi-source data to explore, generate and test business assumptions.




  • 7+ years of experience in generating and sharing insights from data.

  • Proven capability project-leading analysts and engineers, particularly when working across teams

  • Takes responsibility and ownership like no other.

  • Technical experience including expert SQL, and comfort working in one or more scripting languages used in analytics (Python preferred, R, Scala, etc…) required.  Strong skills with Excel and experience with Hadoop and unix shell preferred.

  • Experience with data visualization tools such as Tableau, Qlikview, D3.js, etc.

  • Experience working with SaaS-based recurring subscription business dynamics and metrics including trial conversion, retention and ARPU/C is preferred.

  • Experience working with billing system or product event data is preferred (Additionally preferential to experience with Oracle Billing systems).

  • Entrepreneurial and curious spirit - passionate about data.

  • Undergrad Degree in Quantitative Field.



EOE AA M/F/Vet/Disability