Senior Manager, Sales Analytics

Role overview

CarGurus is looking for a Senior Manager of Sales Analytics to lead the team responsible for data, tools, and analysis supporting Sales and Customer Success across the US, Canada, and the UK. Reporting to the Senior Director of Pricing, Packaging & Analytics, you will guide the team, oversee key go-to-market data assets, and help Sales leaders understand how team structure and sales activity affect retention and net MRR.

The team supports day-to-day decisions with dashboards and tools for sales representatives. This role will expand that support to managers and leadership, strengthen the team's data foundations with a modern, version-controlled stack, and develop useful applications for new data sources, including sales conversation transcript data.

You will lead a multi-level analytics team while staying close to the technical work. You can set standards for analysis and data modeling, develop talent, and work with Sales leaders to turn business questions into tools and analysis they sellers can use regularly.

What you'll do

Lead and develop the analytics team

• Lead analysts across Boston and Dublin, including a first-line manager and a Principal Sales Data Analyst. Set goals, coach and manage performance, and support career development.
• Establish clear career paths for analysts and managers.
• Recruit, hire, and onboard team members as the team's scope evolves.
• Set the team's operating cadence, intake process, and quarterly roadmap. Make priorities and tradeoffs clear to stakeholders.

Own business intelligence for Sales and Service

• Oversee dashboards, hubs, and analytics applications used by Sales representatives, Account Managers, Product Specialists, and Dealer Performance Partners across all three markets.
• Improve visibility for managers and leaders into churn and cancellations, book-of-business health, coverage and activity, and team effectiveness.
• Partner with Sales Enablement and Sales leadership to support adoption and use of the team's tools.

Evaluate sales behaviors and go-to-market initiatives

• Analyze how coverage models, team structures, engagement programs, and sales activity relate to retention, expansion, and net MRR.
• Build repeatable measurement approaches for initiatives such as product launches, engagement programs, and coverage pilots.
• Present findings in QBRs and planning sessions, connecting analysis to the decisions and actions Sales leaders need to consider.

Modernize the team's data stack

• Lead the migration of transformation logic from manually maintained Snowflake views to dbt models and Git-based workflows, with code review, testing, documentation, and clear ownership.
• Set guidance for when logic should be productionized in dbt versus maintained in a team sandbox, partnering with Data Platform Engineering and Analytics Engineering on standards, deployment, and lineage.
• Reduce maintenance burden and key-person risk by consolidating duplicated or legacy objects and moving durable logic into documented, tested models.
• Ensure the team can maintain and operate the solutions it builds.

Develop call transcript data models and use cases

• Own the modeling of Gong conversation data in Snowflake, including calls, participants, and transcripts, and connect it with Salesforce activity and account data.
• Identify and deliver useful applications for transcript data at scale, such as churn and save signals, competitor and pricing mentions, objection patterns, talk-track effectiveness, and inputs to coaching or AI agents. Apply LLM-based extraction where appropriate.
• Establish quality, governance, and appropriate-use standards for conversation data in partnership with Legal, Data Engineering, and Sales leadership.

Steward Sales data across Revenue

• Serve as the steward for Sales-facing data, partnering with Revenue Operations and Enterprise Applications to improve data quality in Salesforce.
• Integrate and model new go-to-market data assets, such as third-party marketplace data, so they can be used across the analytics community.
• Support development of semantic layer for sales data assets to enable AI transformation use cases for analysts and sellers.
• Act as an analytical center of excellence to enable analytically driven functions across the Revenue org.

What you'll bring

• 8+ years of experience in analytics, sales or revenue analytics, business intelligence, or analytics engineering, ideally in a SaaS, marketplace, or subscription business.
• 3+ years leading analytics teams, including managers or senior individual contributors, with experience developing people and building career paths.
• Expert SQL and strong data modeling skills, including the ability to review and troubleshoot others' work.
• Hands-on experience with Snowflake or a similar cloud data warehouse, dbt, and Git-based development. Experience leading a shift from ad hoc or view-based logic to tested, version-controlled models.
• Experience working with unstructured or semi-structured data, such as conversation intelligence, call transcripts, or text, and using LLM or NLP techniques to structure and analyze it.
• Strong knowledge of Salesforce data structures and sales processes, plus experience with enterprise BI tools such as Salesforce CRM Analytics, Omni, Looker, or Tableau.
• Understanding of recurring-revenue metrics, including MRR, churn, retention, expansion, pipeline, and conversion, and how sales coverage and behavior influence them.
• Strong executive communication skills, including the ability to frame decisions and help senior Sales leaders act on analysis.
• A builder's mindset and experience creating self-serve tools and durable data assets, while setting clear priorities for the team.

Python, experience using AI coding tools to accelerate analytics development, and familiarity with automotive retail or dealer software are a plus.