Search Intelligence Manager

Summary

Autodesk is a software company that helps innovators design and make products, buildings, and media. The Search Intelligence Manager will analyze search, website, content, and customer behavior data to build dashboards, identify optimization opportunities, and provide actionable insights across traditional and AI-driven discovery experiences.

Responsibilities

• Build and improve dashboards for search visibility, website engagement, content performance, customer journeys, and conversion trends
• Work with backend data systems, BI tools, Streamlit, Google Search Console, SEMrush, and other sources to collect, validate, analyze, and visualize performance data
• Diagnose search and discovery trends across impressions, clicks, CTR, rankings, landing pages, engagement, conversion, AI referrals, and emerging LLM-driven discovery paths
• Analyze behavioral patterns for users arriving through organic search and AI-driven discovery, including landing-page behavior, content paths, drop-off points, and conversion signals
• Identify SEO, AEO, content, and digital experience optimization opportunities based on data, customer behavior, and business impact
• Partner with analytics, data engineering, search, content, marketing, and technical teams to define KPI logic, reporting needs, and source-of-truth measurement approaches
• QA datasets, dashboards, reporting outputs, and scoring frameworks to ensure accuracy, consistency, and stakeholder trust
• Support prioritization by combining performance data, business value, customer intent, content metadata, and optimization opportunity
• Prepare concise performance summaries, visualizations, and insight narratives that help teams make smarter decisions
• Stay current on search behavior, AI-driven discovery, analytics practices, and emerging measurement approaches

Skills

• 3–5+ years of experience in digital analytics, marketing analytics, BI/reporting, analytics engineering, growth analytics, search analytics, or a related analytical role
• Experience working with backend data systems, data warehouses, BI platforms, dashboards, and large datasets
• Strong SQL or equivalent data-querying experience, with the ability to pull, join, clean, validate, and analyze data from multiple sources
• Experience building dashboards, reporting tools, or lightweight data applications using tools such as Streamlit, Looker, Tableau, Power BI, or similar platforms
• Familiarity with Google Search Console and SEMrush data, including search visibility, query, landing-page, and keyword performance trends
• Ability to analyze customer behavior, journey paths, funnel performance, or conversion patterns using web analytics, BI tools, or backend datasets
• Strong data QA skills, including validating metric definitions, identifying discrepancies, documenting assumptions, and ensuring reporting accuracy
• Ability to translate complex data into clear insights, recommendations, and business narratives
• Strong problem-solving skills, attention to detail, and willingness to learn quickly in a fast-moving search and AI discovery landscape
• Collaborative mindset with the ability to work across analytics, data engineering, search, content, marketing, and technical teams
• Familiarity with SEO concepts, keyword strategy, content performance, search visibility, or digital marketing metrics
• Familiarity with AEO or AI-driven search concepts such as AI Overviews, LLM referrals, prompt monitoring, citation visibility, share of answer, or zero-click behavior
• Experience with Python, R, dbt, BigQuery, Snowflake, Databricks, ETL workflows, data modeling, or analytics engineering practices
• Experience combining search data, web analytics data, content metadata, CRM/conversion data, and customer behavior data to generate recommendations
• Experience developing KPI frameworks, prioritization models, scoring systems, or source-of-truth reporting documentation
• Experience with Adobe Analytics or similar web analytics platforms

Qualifications

Must Haves

• 3–5+ years of experience in digital analytics, marketing analytics, BI/reporting, analytics engineering, growth analytics, search analytics, or a related analytical role
• Experience working with backend data systems, data warehouses, BI platforms, dashboards, and large datasets
• Strong SQL or equivalent data-querying experience, with the ability to pull, join, clean, validate, and analyze data from multiple sources
• Experience building dashboards, reporting tools, or lightweight data applications using tools such as Streamlit, Looker, Tableau, Power BI, or similar platforms
• Familiarity with Google Search Console and SEMrush data, including search visibility, query, landing-page, and keyword performance trends
• Ability to analyze customer behavior, journey paths, funnel performance, or conversion patterns using web analytics, BI tools, or backend datasets
• Strong data QA skills, including validating metric definitions, identifying discrepancies, documenting assumptions, and ensuring reporting accuracy
• Ability to translate complex data into clear insights, recommendations, and business narratives
• Strong problem-solving skills, attention to detail, and willingness to learn quickly in a fast-moving search and AI discovery landscape
• Collaborative mindset with the ability to work across analytics, data engineering, search, content, marketing, and technical teams

Nice to Haves

• Familiarity with SEO concepts, keyword strategy, content performance, search visibility, or digital marketing metrics
• Familiarity with AEO or AI-driven search concepts such as AI Overviews, LLM referrals, prompt monitoring, citation visibility, share of answer, or zero-click behavior
• Experience with Python, R, dbt, BigQuery, Snowflake, Databricks, ETL workflows, data modeling, or analytics engineering practices
• Experience combining search data, web analytics data, content metadata, CRM/conversion data, and customer behavior data to generate recommendations
• Experience developing KPI frameworks, prioritization models, scoring systems, or source-of-truth reporting documentation
• Experience with Adobe Analytics or similar web analytics platforms

Benefits

• Annual cash bonuses
• Commissions for sales roles
• Stock grants
• A comprehensive benefits package