Senior Analytics Engineer - GTM

gomotive; United States; Hybrid; USD 120,000 - 180,000; Full time

Job summary

gomotive is seeking a senior data professional to build the data foundation that powers go-to-market planning and performance analysis. The role combines sales-domain expertise with advanced SQL, data modeling, and dashboarding to deliver trusted metrics and scalable data products.

You will collaborate with analysts, design pipelines and semantic models, and enable AI-driven data access while maintaining clear documentation and governance across the analytics stack.

Qualifications

• Seven or more years of experience in data engineering, analytics engineering, or data analytics.
• Deep expertise in dimensional data modeling and modern data-warehouse design.
• Advanced SQL skills and experience with columnar analytics platforms such as Snowflake or BigQuery.
• Strong knowledge of Salesforce's data model and other go-to-market systems.

Responsibilities

• Set and deliver the go-to-market data roadmap, prioritizing durable, scalable products for sales and growth teams.
• Build and maintain pipelines, warehouse models, and data marts supporting headcount planning, quota attainment, pipeline analysis, and sales effectiveness.
• Create reliable dashboards and reporting that make core performance measures understandable and actionable across the organization.
• Partner with analysts to improve their use of datasets and data tools, and produce clear documentation, technical specifications, and tutorials.
• Work across the analytics stack, from ad hoc analysis and reporting through pipeline architecture and semantic modeling.

Skills

Advanced SQL

Dimensional modeling

Data warehouse design

Snowflake or BigQuery

dbt

Git

BI tools

Salesforce data model

Go-to-market systems

Tools

Snowflake

BigQuery

dbt

Git

BI tools

Job description

Role overview

Build the data foundation that helps go-to-market teams plan, measure, and improve business performance. Working within a centralized analytics and data organization, this senior individual contributor will combine sales-domain expertise with advanced SQL, data modeling, pipeline development, dashboarding, and clear communication to establish trusted metrics and scalable data products.

Responsibilities

• Set and deliver the go-to-market data roadmap, prioritizing durable, scalable products for sales and growth teams.
• Build and maintain pipelines, warehouse models, and data marts supporting headcount planning, quota attainment, pipeline analysis, and sales effectiveness.
• Create reliable dashboards and reporting that make core performance measures understandable and actionable across the organization.
• Partner with analysts to improve their use of datasets and data tools, and produce clear documentation, technical specifications, and tutorials.
• Work across the analytics stack, from ad hoc analysis and reporting through pipeline architecture and semantic modeling.
• Develop semantic models and evaluation processes for AI tools that allow sales operators to query business data using natural language.

Requirements

• Seven or more years of experience in data engineering, analytics engineering, or data analytics.
• Deep expertise in dimensional data modeling and modern data-warehouse design.
• Advanced SQL skills and experience with columnar analytics platforms such as Snowflake or BigQuery.
• Strong knowledge of Salesforce's data model and other go-to-market systems.
• Experience with dbt, Git, and business-intelligence tools.
• Experience supporting sales, sales operations, sales compensation, and finance stakeholders.
• Ability to explain complex data concepts clearly to executives, business partners, engineers, and senior individual contributors.

Nice to have

• Experience building AI-oriented data capabilities such as semantic layers, context-management systems, or evaluation frameworks.
• Direct experience with Hex or comparable analytics environments.
• Meticulous attention to detail and strong independent project-management skills.
• Familiarity with AI-assisted development while maintaining clean, maintainable code, models, and documentation.

Benefits and work setup

Some interviews or new-hire training sessions may take place in person at a global office, depending on the circumstances.