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Staff Analytics Engineer

1 day, 11 hours ago
United States
Full-time
Lead
Analytics Engineer
Data Science and Analytics
dbt Git Looker Python Snowflake SQL
Apply Now
HubSpot

HubSpot

HubSpot provides a comprehensive cloud-based CRM platform that integrates marketing, sales, service, and operations tools to help businesses attract, engage, and delight customers effectively.

Media
5K-10K
Founded 2006
View All Jobs 110

Description

  • Build and optimize data pipelines and analytical tools for scale.
  • Own and evolve core platform assets, AE tooling, reusable patterns, and automation for the analytics engineering team.
  • Contribute to the composable agentic AE delivery system that automates the delivery lifecycle from context to merged pull request.
  • Design and maintain semantic models that serve as a trusted foundation for analytics and AI consumption.
  • Build internal AI agents and data-grounded tools, including integrations through RPC-based capabilities via MCP servers.
  • Design and implement cost strategies for shared data assets, pipelines, and compute usage.
  • Define and deploy scalable data ingestion, replication, and transfer patterns across systems.
  • Build scalable data models to analyze key parts of the HubSpot business.
  • Expand dbt patterns and macros to support flexible and extensible data structures.
  • Drive data observability and pipeline reliability using tools such as Monte Carlo.
  • Establish scalable patterns and standards for analytical application development in Hex.
  • Lead working groups, scope requirements, and guide projects through the full lifecycle.
  • Maintain detailed documentation of data pipelines, processes, and best practices.
  • Partner with stakeholders to solve business problems with technical solutions.
  • Guide the professional development of the team through technical leadership.

Requirements

  • Expert knowledge of modern data tools such as Snowflake, dbt, and Looker.
  • Extensive proficiency in SQL, data modeling, ETL, ELT, and data transformation.
  • Deep dbt expertise, including advanced modeling patterns, macros, and package development.
  • Experience developing slowly changing dimension (SCD) tables from multiple sources.
  • Successful experience leading complex, cross-functional data initiatives from ambiguous problem to production.
  • Experience building or maintaining shared data platform assets, developer toolkits, or internal frameworks.
  • Experience designing semantic models or metric layers for analytics or AI consumption.
  • Proficiency with AI-assisted development tools such as Claude Code, including agentic pipeline design and composable, skill-based workflows.
  • Comfort building AI agents and integrating external tools and services via MCP servers.
  • Experience using version control tools such as GitHub Enterprise Cloud.
  • A DevOps mindset with automation, collaboration, continuous improvement, and a strong focus on user needs and frequent iteration.
  • Strong communication skills and the ability to distill technical solutions into business terms.
  • Experience with Python is a plus, but not required.

Benefits

  • Annual cash compensation range of $138,500 to $221,600 USD.
  • Cash compensation may include base salary, on-target commission for eligible roles, and annual bonus targets.
  • Some roles are eligible for equity participation through restricted stock units (RSUs).
  • Some roles may also be eligible for overtime pay.
  • Compensation packages are tailored to your skills, experience, qualifications, and other job-related reasons.
  • Benefits and perks are offered as part of the total compensation package.
  • Flexible work environment with both remote and office options, plus in-person onboarding for Engineering roles.

Interested in this position?

Apply directly on the company website

Apply Now

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