Note: The job is a remote job and is open to candidates in USA. HubSpot is an AI-powered customer platform dedicated to helping organizations grow better. The Staff Analytics Engineer will join the Data & AI Foundations team to design and build a modern data foundation that supports analytic and machine learning products, enhancing decision-making across the organization.
Responsibilities
- Build and optimize the performance of data pipelines and analytical tools for scale
- Own and evolve core platform assets, AE tooling, reusable patterns, and automation that raise the floor for every AE on the team
- Contribute to our composable agentic AE delivery system, a pipeline of AI-powered skills that automates the full delivery lifecycle from context to merged PR
- Design and maintain semantic models that serve as the trusted, reusable foundation for analytics and AI consumption across the organization
- Build internal AI agents and data-grounded tools, integrating 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
- Foster innovation with emerging technologies and by staying current with industry trends
- Guide professional development of the team through technical leadership
- Partner with stakeholders to solve business problems with technical solutions
- Build out scalable data models to analyze key parts of the HubSpot business
- Expand our suite of dbt patterns and macros to enable flexible and easily extensible data structures
- Drive data observability and pipeline reliability using tools like Monte Carlo
- Establish scalable patterns and standards for analytical application development in Hex
- Lead working groups, scope requirements, and usher projects through the entire lifecycle
- Maintain detailed documentation of data pipelines, processes, and best practices
Skills
- 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 utilizing version control tools (such as GitHub Enterprise Cloud)
- A DevOps mindset characterized by automation, collaboration, continuous improvement, and a hyperfocus on user needs and frequent iteration
- Strong communication skills and ability to distill technical solutions into business terms
- Experience with Python is a plus, but not required
Benefits
- On-target commission for employees in eligible roles
- Annual bonus targets under HubSpot’s bonus plan for eligible roles
- Eligible to participate in HubSpot’s equity plan to receive restricted stock units (RSUs)
- May also be eligible for overtime pay
- Tailored individual compensation packages based on skills, experience, qualifications, and other job-related reasons
- Flexibility and connection for Remote employees or those working from the Office
- In-person onboarding at a regional HubSpot office for Engineering team members
- In-person events such as Product Group Summit and other gatherings for broader Product team members
- Accommodations or assistance due to a disability
- Support for candidates who may need alternative arrangements due to travel limitations or other reasons
Company Overview
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