Job description

We are hiring a Senior Staff Business Data Analyst to build the reporting, analytical, and AI layer on top of the sales data foundation — the views, semantic models, and dashboards the sales organization actually makes decisions with, and the data architecture that makes those views trustworthy. This is a senior individual contributor role. You are expected to operate at organizational scope: choosing what gets built, designing the models other analysts build on, setting the standard for how sales reporting works, and raising the capability of the analysts around you. The work runs from schema design through to the number a sales leader reads on a Monday morning, and you'll own the whole span rather than a slice of it. Responsibilities What you'll own: • Reporting and dashboard architecture. Design and build the dashboards and reporting views the sales organization runs on — pipeline, coverage, win rate, forecast attainment, partner performance — as a coherent, maintainable set rather than an accumulating pile of one-off requests. You'll decide what becomes a governed asset, what stays ad hoc, and what should be retired. • Semantic and consumption models. Build the layer between certified base tables and the people consuming them: reusable views, defined grains, conformed dimensions, and metric logic implemented consistently so that two dashboards asking the same question can't disagree. • Data architecture contribution. Work alongside Data Operations on the underlying model — account, opportunity, contact, activity, contact role, campaign membership, account team, lead. You'll be one of the voices deciding how these fit together, and a primary source of the requirements that shape them, because you'll be the one whose reporting breaks if the grain or the keys are wrong. • Identity and taxonomy in practice. Sales data arrives keyed differently in every system. You'll work daily in the resolution of account, company, firm, and customer identifiers, and in the product line / product family taxonomy — and you'll be the one who catches it when a metric resolves differently depending on which side of a join you're standing on. • Metric definition and integrity. Contribute to and defend canonical KPI definitions: the base query, the grain, the exclusions, the edge cases. Where a number is contested, you'll be the person who can reconstruct exactly how it was calculated and why. • Analysis that changes decisions. Beyond reporting, do the analytical work behind coverage models, buying-group completeness, funnel diagnostics, and territory and channel performance — for both direct and partner-led motions. • Technical leadership. Set patterns, review other analysts' models, mentor, and write down the standards. Much of your impact will come through work you didn't personally build. Qualifications What you'll bring: Required • 4+ years in business intelligence, analytics engineering, or data analysis, including experience as the senior technical voice on ambiguous, cross-team problems. • Expert SQL. You can develop complex queries and structures that resolve high volume datasets and schemas across lines of business. • Strong analytical data modeling: dimensional design, grain discipline, conformed dimensions, slowly changing dimensions, and the judgment to know when to denormalize. • Deep hands-on experience with a modern BI platform (Tableau, Power BI, Looker, or equivalent) — including semantic layer design, extract and performance tuning, and governance of published assets. • Direct experience with CRM data, Salesforce strongly preferred. You know the standard objects, their quirks, and what silently breaks when you join them without care. • Experience building reporting that others depend on operationally, including the unglamorous parts: freshness expectations, breakage handling, change communication, and deprecation. • Ability to work directly with sales leaders — translating a vague question into a defensible metric, and pushing back when the metric they asked for won't answer the question they have. Preferred • Experience supporting sales, revenue, or partner/channel operations. • Experience with partner or channel-led models, and reporting on partner relationships as first-class entities rather than as an afterthought on a direct-sales schema. • Cloud warehouse or datalake depth (Databricks, Snowflake, or equivalent), transformation frameworks, orchestration, and version-controlled analytics code. • Python or equivalent for analysis beyond what SQL handles well. • Experience reporting through a major system migration, keeping numbers continuous while the underlying sources move. • Familiarity with conversation-intelligence and sales-engagement data, and the data-quality realities of seller-created records. Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Mountain View $184,000 - $249,000

Requirements

Must-haves

Technical leadership. Set patterns, review other analysts' models, mentor, and write down the standards. Much of your impact will come through work you didn't personally build.
4+ years in business intelligence, analytics engineering, or data analysis, including experience as the senior technical voice on ambiguous, cross-team problems.
Expert SQL. You can develop complex queries and structures that resolve high volume datasets and schemas across lines of business.
Strong analytical data modeling: dimensional design, grain discipline, conformed dimensions, slowly changing dimensions, and the judgment to know when to denormalize.
Deep hands-on experience with a modern BI platform (Tableau, Power BI, Looker, or equivalent) — including semantic layer design, extract and performance tuning, and governance of published assets.
Experience building reporting that others depend on operationally, including the unglamorous parts: freshness expectations, breakage handling, change communication, and deprecation.
Ability to work directly with sales leaders — translating a vague question into a defensible metric, and pushing back when the metric they asked for won't answer the question they have.

Nice-to-haves

Direct experience with CRM data, Salesforce strongly preferred. You know the standard objects, their quirks, and what silently breaks when you join them without care.
Experience supporting sales, revenue, or partner/channel operations.
Experience with partner or channel-led models, and reporting on partner relationships as first-class entities rather than as an afterthought on a direct-sales schema.
Cloud warehouse or datalake depth (Databricks, Snowflake, or equivalent), transformation frameworks, orchestration, and version-controlled analytics code.
Python or equivalent for analysis beyond what SQL handles well.
Experience reporting through a major system migration, keeping numbers continuous while the underlying sources move.
Familiarity with conversation-intelligence and sales-engagement data, and the data-quality realities of seller-created records.
Mountain View $184,000 - $249,000

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aisqlpython

Platform: career-feeds
Effort: medium