Business Intelligence Analyst

Summary

and the job listing Expires on September 22, 2026The AOS Growth Analytics team is hiring a Data & Business Analyst to support operational analysis and reporting across Autodesk Operation Solutions go‑to‑market functions. This role sits at the intersection of business operations, data analysis, BI reporting, and analytics enablement. You will help AOS teams understand performance, build reports and monitor key metrics, improve recurring business cadences, and turn data into practical actions. The role is hands‑on. You will write SQL, build and maintain dashboards, build data models, document metric definitions, and help stakeholders use analytics more effectively. This is a strong fit for someone with 2–5 years of analytics experience who enjoys working close to the business, is comfortable with ambiguity, and has built dashboards, reporting processes, analytical workflows, or operational tools from scratch. The ideal candidate is not just a dashboard builder and not just a business generalist. They can understand the business context, investigate the data, explain what is happening, and help teams act on the insight.What Makes This Role Interesting: This role is operational, hands‑on, and close to the business. You will help build the analytics muscle for AOS Growth Analytics: the dashboards people rely on, the metrics they use in recurring reviews, the reporting processes that reduce manual work, and the analytical explanations that help teams understand what is changing and why. You will also have room to build from scratch. Some problems will not come with clean requirements, perfect data, or an existing dashboard. You will need to ask good questions, create structure, prototype solutions, and improve them with stakeholder feedback.ResponsibilitiesSupport AOS Growth Analytics by building, maintaining, and improving operational dashboards, recurring reports, and business review materialsPartner with AOS go‑to‑market stakeholders to understand business questions, clarify requirements, define metrics, and translate needs into practical analytics deliverablesUse AI tools responsibly to improve analytics workflows, such as summarizing trends, drafting first‑pass business narratives, accelerating exploratory analysis, identifying anomalies, and automating repetitive reporting tasksUse SQL, primarily in Snowflake or similar cloud data platforms, to extract, validate, join, and analyze data from multiple sourcesBuild and maintain dashboards that help stakeholders monitor performance, identify trends, and understand operational driversPartner with data engineering or analytics engineering teams on data modeling needs, including dbt or similar modeling workflows, while not being expected to fully own production data pipelinesCreate clean, repeatable analysis for recurring business cadences, including weekly/monthly performance reviews, operational health checks, and leadership readoutsInvestigate metric movement, anomalies, data quality issues, and business process gaps; summarize findings clearly and recommend next stepsHelp define and document metric logic, data sources, dashboard usage, and known limitations so stakeholders have a trusted source of truthWork across multiple AOS‑adjacent functions while staying primarily focused on AOS Growth Analytics prioritiesMinimum Qualifications2–5 years of experience in data analysis, business analysis, business intelligence, GTM analytics, operations analytics, revenue operations, sales operations, customer success operations, or a related analytics roleBachelor degree in Business Analytics, Statistics, Engineering, CS, DS, or a related field; or equivalent practical experienceStrong AI analytics skills, including analytics agent deployment and orchestration, & assisted coding for analytics purposes, to improve analysis, reporting, insight generation, workflow automation, or business communicationStrong SQL skills and experience working with data warehouses such as Snowflake or similar platformsExperience building dashboards and reports in Power BI or similar BI toolsWorking knowledge of data modeling concepts; experience with dbt or similar modeling tools is a plusAbility to gather business requirements, clarify ambiguous asks, and translate them into dashboards, metrics, analyses, or operational reportingStrong analytical problem‑solving skills, including the ability to investigate root causes, validate data, and explain metric movementStrong communication skills with technical and non‑technical stakeholdersComfort working in an operational environment with evolving priorities, imperfect data, and recurring reporting needsDemonstrated experience building something from scratch, such as a dashboard, reporting workflow, metric framework, analysis package, process improvement, or internal toolPreferred QualificationsExperience supporting GTM, sales, customer success, marketing, revenue operations, product operations, business operations, or SaaS analyticsExperience with Snowflake, dbt, Power BI, Scripting Languages or similar modern analytics toolsExperience creating metric documentation, dashboard guides, stakeholder enablement materials, or self‑service analytics resourcesUnderstanding of SaaS or subscription business concepts such as pipeline, adoption, usage, retention, conversion, expansion, productivity, or customer lifecycle metricsAbility to balance speed and accuracy: moving quickly while still checking assumptions, validating data, and documenting limitationsThe Ideal CandidateThe strongest candidate is a hands‑on analyst with business judgment.They can write SQL, build a Power BI dashboard, understand a GTM stakeholder question, validate whether the data is trustworthy, deploy AI agents to answer analytics questions, and explain the answer in plain language. They are comfortable operating in the middle: close enough to the data to be technical, and close enough to the business to know what matters.They are also a builder. They have created useful things from scratch before and are comfortable improving them over time.Salary TransparencySalary transparencySalary is one part of Autodesk's competitive compensation package. For Canada based roles, we expect a starting base salary between $80,000 and $117,700. Offers are based on the candidate's experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.#J-18808-Ljbffr

Job Description

and the job listing Expires on September 22, 2026The AOS Growth Analytics team is hiring a Data & Business Analyst to support operational analysis and reporting across Autodesk Operation Solutions go‑to‑market functions. This role sits at the intersection of business operations, data analysis, BI reporting, and analytics enablement. You will help AOS teams understand performance, build reports and monitor key metrics, improve recurring business cadences, and turn data into practical actions. The role is hands‑on. You will write SQL, build and maintain dashboards, build data models, document metric definitions, and help stakeholders use analytics more effectively. This is a strong fit for someone with 2–5 years of analytics experience who enjoys working close to the business, is comfortable with ambiguity, and has built dashboards, reporting processes, analytical workflows, or operational tools from scratch. The ideal candidate is not just a dashboard builder and not just a business generalist. They can understand the business context, investigate the data, explain what is happening, and help teams act on the insight.What Makes This Role Interesting: This role is operational, hands‑on, and close to the business. You will help build the analytics muscle for AOS Growth Analytics: the dashboards people rely on, the metrics they use in recurring reviews, the reporting processes that reduce manual work, and the analytical explanations that help teams understand what is changing and why. You will also have room to build from scratch. Some problems will not come with clean requirements, perfect data, or an existing dashboard. You will need to ask good questions, create structure, prototype solutions, and improve them with stakeholder feedback.ResponsibilitiesSupport AOS Growth Analytics by building, maintaining, and improving operational dashboards, recurring reports, and business review materialsPartner with AOS go‑to‑market stakeholders to understand business questions, clarify requirements, define metrics, and translate needs into practical analytics deliverablesUse AI tools responsibly to improve analytics workflows, such as summarizing trends, drafting first‑pass business narratives, accelerating exploratory analysis, identifying anomalies, and automating repetitive reporting tasksUse SQL, primarily in Snowflake or similar cloud data platforms, to extract, validate, join, and analyze data from multiple sourcesBuild and maintain dashboards that help stakeholders monitor performance, identify trends, and understand operational driversPartner with data engineering or analytics engineering teams on data modeling needs, including dbt or similar modeling workflows, while not being expected to fully own production data pipelinesCreate clean, repeatable analysis for recurring business cadences, including weekly/monthly performance reviews, operational health checks, and leadership readoutsInvestigate metric movement, anomalies, data quality issues, and business process gaps; summarize findings clearly and recommend next stepsHelp define and document metric logic, data sources, dashboard usage, and known limitations so stakeholders have a trusted source of truthWork across multiple AOS‑adjacent functions while staying primarily focused on AOS Growth Analytics prioritiesMinimum Qualifications2–5 years of experience in data analysis, business analysis, business intelligence, GTM analytics, operations analytics, revenue operations, sales operations, customer success operations, or a related analytics roleBachelor degree in Business Analytics, Statistics, Engineering, CS, DS, or a related field; or equivalent practical experienceStrong AI analytics skills, including analytics agent deployment and orchestration, & assisted coding for analytics purposes, to improve analysis, reporting, insight generation, workflow automation, or business communicationStrong SQL skills and experience working with data warehouses such as Snowflake or similar platformsExperience building dashboards and reports in Power BI or similar BI toolsWorking knowledge of data modeling concepts; experience with dbt or similar modeling tools is a plusAbility to gather business requirements, clarify ambiguous asks, and translate them into dashboards, metrics, analyses, or operational reportingStrong analytical problem‑solving skills, including the ability to investigate root causes, validate data, and explain metric movementStrong communication skills with technical and non‑technical stakeholdersComfort working in an operational environment with evolving priorities, imperfect data, and recurring reporting needsDemonstrated experience building something from scratch, such as a dashboard, reporting workflow, metric framework, analysis package, process improvement, or internal toolPreferred QualificationsExperience supporting GTM, sales, customer success, marketing, revenue operations, product operations, business operations, or SaaS analyticsExperience with Snowflake, dbt, Power BI, Scripting Languages or similar modern analytics toolsExperience creating metric documentation, dashboard guides, stakeholder enablement materials, or self‑service analytics resourcesUnderstanding of SaaS or subscription business concepts such as pipeline, adoption, usage, retention, conversion, expansion, productivity, or customer lifecycle metricsAbility to balance speed and accuracy: moving quickly while still checking assumptions, validating data, and documenting limitationsThe Ideal CandidateThe strongest candidate is a hands‑on analyst with business judgment.They can write SQL, build a Power BI dashboard, understand a GTM stakeholder question, validate whether the data is trustworthy, deploy AI agents to answer analytics questions, and explain the answer in plain language. They are comfortable operating in the middle: close enough to the data to be technical, and close enough to the business to know what matters.They are also a builder. They have created useful things from scratch before and are comfortable improving them over time.Salary TransparencySalary transparencySalary is one part of Autodesk's competitive compensation package. For Canada based roles, we expect a starting base salary between $80,000 and $117,700. Offers are based on the candidate's experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.#J-18808-Ljbffr