Senior II Data Engineer, GTM Data

Revenue Operations

Remote - USA

HubSpot’s mission is to Help Millions of Companies Grow Better, and we believe recent advances in AI/ML will allow our internal Go-to-Market (GTM) teams to more effectively serve even more companies, helping them to grow. We’re seeking a talented Senior Data Engineer to join our GTM Data and Systems team as part of a newly-formed GTM AI team supporting our internal Sales and Customer Success (CS) clients through the delivery of scalable AI/ML and other data products to improve the efficiency and efficacy of frontline Sales and Customer Success reps and solve for their pain points.

You will be joining a high-growth, high-powered GTM Data team of Analytic Engineers, Data Scientists, Data Engineers, and ML Engineers that deeply values intellectual curiosity, collaboration, and autonomy. The algorithms, insights, and data products we develop allow our Sales and CS reps to more effectively support our prospects and customers. It’s an exciting opportunity to make an enormous impact in a rapidly growing space–we’ve got big plans and want talented, passionate engineers to help us achieve them! (HubSpot is early in its GTM AI maturity curve, which provides a unique opportunity for enormous impact.)

You will work collaboratively not only with other Data and ML Engineers on the team, but also the ML Ops team (who provide model deployment, monitoring, and orchestration support), the GTM Data Platform team (who provide analytic feature stores and access to new data sources), our Flywheel Product team (who provide the front-end experiences reps interact with on a daily basis), and many other teams.

Objectives of this Role

• Build scalable, fault-tolerant data pipelines for both batch and real time use cases, ensuring on- and off-line consistency 
• Collaborate closely with tech leads, Analytics Engineers, and ML Engineers to design and implement scalable data pipelines to support model inferences and feature stores
• Build out APIs to make feature stores and inferences accessible to a variety of applications
• Work with ML engineers to design and implement feedback loops to allow the AI/ML solutions to learn and improve over time
• Monitor application performance, diagnose bottlenecks, and implement performance improvements as needed
• Implement robust error-handling mechanisms and ensure the application's fault tolerance and high availability
• Query, integrate, analyze, and preprocess rich and complex datasets (both structured and unstructured) to extract relevant features and insights
• Participate in code reviews, extensive testing, and documentation, ensuring continued/improved quality and maintainability of the codebase

About you:

• Degree in computer science, statistics, applied mathematics, economics, or other quantitative discipline
• 3+ years experience in data engineering with multiple pipelines deployed in operational settings
• Proven track record of delivering high-performance back-end applications with low latency
• Hands-on experience with highly-available databases and designing data-stores for low-latency data retrieval (including both structured and unstructured data)
• Proficiency designing and executing scalable data pipelines using kafka
• Strong understanding of RESTful API design principles and best practices
• Experience designing robust systems and monitoring strategies to ensure high-levels of quality and availability, preferably in the context of AI/ML workloads
• Extensive familiarity with Snowflake (or similar cloud warehouse), SQL, as well as dbt and jinja templating
• Familiarity with standard deployment stack (Docker, Kubernetes. etc.)
• Familiarity with CI/CD systems (e.g. GitHub Actions, Jenkins, etc.)
• Familiarity with monitoring & alerting systems (Monte Carlo, Cloudwatch, DataDog, GreatExpectations, etc.)
• Able to clearly communicate highly technical concepts to business leaders in both slides and memos
• Curious, creative, collaborative problem solver with experience delivering iterative solutions to difficult problems

Bonus points:

• MS or PhD in quantitative field
• Exceptional Java programming skills
• Familiarity with a breadth of machine learning/AI techniques and their applications
• Prior academic or industrial experience with LLM pipelines
• Prior experience supporting GTM teams or functions, especially in B2B SaaS companies

Cash compensation range: 186300-279500 USD Annually

This resource will help guide how we recommend thinking about the range you see. Learn more about HubSpot’s compensation philosophy from Katie Burke, HubSpot’s Chief People Officer.

The cash compensation above includes base salary, on-target commission for employees in eligible roles, and annual bonus targets under HubSpot’s bonus plan for eligible roles. In addition to cash compensation, all HubSpotters are eligible to participate in HubSpot’s equity plan to receive restricted stock units (RSUs). Some roles may also be eligible for overtime pay. Individual compensation packages are based on a few different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

We know that benefits are also an important piece of your total compensation package. To learn more about what’s included in total compensation, check out some of thebenefits and perks HubSpot offers to help employees grow better.

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We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates, so please don’t hesitate to apply — we’d love to hear from you.

If you need accommodations or assistance due to a disability, please reach out to us using this form. This information will be treated as confidential and used only for the purpose of determining an appropriate accommodation for the interview process.

Germany Applicants: (m/f/d) - link to HubSpot's Career Diversity page here.

About HubSpot

HubSpot (NYSE: HUBS) is a leading customer relationship management (CRM) platform that provides software and support to help businesses grow better. We build marketing, sales, service, and website management products that start free and scale to meet our customers’ needs at any stage of growth. We’re also building a company culture that empowers people to do their best work. If that sounds like something you’d like to be part of, we’d love to hear from you.

You can find out more about our company culture in the HubSpot Culture Code, which has more than 5M views, and learn about our commitment to creating a diverse and inclusive workplace, too. Thanks to the work of every employee globally, HubSpot was named the #2 Best Place to Work on Glassdoor in 2022, and has been recognized for award-winning culture by Great Place to Work, Comparably, Fortune, Entrepreneur, Inc., and more.

Headquartered in Cambridge, Massachusetts, HubSpot was founded in 2006. Today, thousands of employees work across the globe in HubSpot offices and remotely. Visit our careers website to learn more about culture and opportunities at HubSpot.

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