We are seeking an Analytics Engineer to be responsible for the data processing architecture and data modeling that will power our Business Technology (BizTech) teams. BizTech at HubSpot includes IT Infrastructure, Global Helpdesk, Collaboration, and Employee Technology. In this role, you will act as a full stack data analyst to design and build the data infrastructure and models that will enable BizTech to make smarter investment decisions and better understand the impact of our work. You will also partner with cross-functional teams to use data to drive strategic and operational innovation throughout HubSpot.

In this role, you'll get to:

• Build and own the data solutions that our  enterprise system owners rely on to know what’s working and what’s not. This includes all data modeling and helping to scale our data collection and reporting capabilities.
• Work closely with other business systems teams to drive automation from your single source of truth reporting. 
• Develop best practices for collecting, cleaning, and maintaining BizTech’s  data.
• Partner with cross-functional teams (including our central Business Intelligence team and  other relevant Operations teams) to identify opportunities for improving systems, processes, and decision making.
• Help make strategic programs more data-driven, including: improving our employee experience, improving our global approach to HelpDesk support, improving how we communicate and collaborate, and determining how to scale our culture.

We are looking for people who:

• Have advanced, technical, hands-on experience with data model development, data visualization, data warehouse development, data preparation, and analytics tools
• Have a combination of deep technical know-how and remarkable business acumen; we want people who will make consistently great decisions about where to spend their time and how to build their solutions
• Have experience translating desired business outcomes into a set of technical tasks that build towards the desired deliverables and outcomes
• Have experience working with and maintaining the confidentiality of sensitive employee data
• Use custom SQL for developing data pipelines and derived tables, experience with DBT or Airflow is a nice to have
• Are very comfortable developing scripts to support data and analytics automation 
• Have experience building reporting infrastructure at scale
• Possess strong analytical skills to determine data integrity and ensure the right controls are in place. 
• Have experience with SaaS BI tools like Looker or Tableau
• Are comfortable operating in a constantly changing global environment and have an eye for how to scale systems/processes.
• Are highly proficient in SQL. Proficiency in Python or R is also valuable.

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.

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 through. 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 #4 Best Place to Work on Glassdoor in 2021, 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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