Principal Analytics Engineer

Our goal in RevOps is to embed advanced analytics and algorithmic intelligence into the DNA of decision-making across Flywheel. Flexible, well-connected, well-architected data are the backbone of our strategy, along with the Analytics Engineers who create that landscape. Flywheel is expected to grow to 12k employees by 2025–to effectively scale algorithmic intelligence and advanced analytics to support the needs of the future Flywheel, we need to design and build a modern data foundation for efficient models and analyses. Your work will directly support analytic and ML products that will change the way we make decisions within Flywheel at HubSpot.

We’re looking for Analytic Engineers with a strong interest in building and maintaining flexible, reusable architecture for our highest value data assets. You’ll have the opportunity to learn about data science and MLOps, as well as Sales, Customer Success, and our customers’ journeys with HubSpot. In this cross-functional role, you will develop a deep understanding of the business and analytics priorities to motivate solutions that will unlock our ability to scale and drive actionable insights.

In this role, you’ll get to:

Help shape the data strategy for RevOps and Flywheel more generally
Collaborate with technical and non-technical stakeholders, bridging the gap between business problem and technical solution
Design and implement modern, scalable data assets for modeling and analysis, including: (1) feature stores for multiple entity levels, (2) use-case agnostic staging layers, and (3) customer journey data models
Expand our suite of dbt patterns and macros to enable flexible and easily extensible data structures
Work on building our data science flywheel: from instrumentation to model pipelines to inference and predictions to outcomes and back
Collaborate with engineers, data scientists, and business stakeholders from across HubSpot
Scope requirements with internal stakeholders and lead working groups to usher projects through their entire lifecycle while building clear roadmaps for cross-functional team members

We are looking for someone with:

Expert knowledge of modern data tools (especially Snowflake and dbt, Looker is nice to have)
Strong communication skills and ability to bridge between business leaders, engineers, and data scientists
Experience designing and developing SCD tables from multiple log/audit file sources
Successful experience building complex, cross-functional data projects
Experience distilling complex ideas and data for both executives and front-line reps
Creative problem solving skills to identify flexible solutions to business questions
Insatiable curiosity and interest in learning new things

Cash compensation range: 150,000-175,000 USD Annually

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