About the job
Grafana Labs is a pioneering open-source organization that operates with a remote-first approach. With over 20 million users globally, our renowned Grafana visualization tool is utilized to monitor a diverse range of applications, from environmental changes to the performance of beehives. Our visually striking dashboards have gained recognition at prestigious events such as NASA launches, Wimbledon, and the Tour de France. Supporting over 3,000 companies, including industry giants like Bloomberg, JPMorgan Chase, and eBay, we empower businesses to effectively manage their observability strategies using the Grafana LGTM Stack.
As we expand rapidly, we remain committed to our unique attributes: a legacy rooted in open-source principles, a collaborative global culture, and a dedication to impactful work. Our team thrives in an environment driven by innovation, transparency, autonomy, and trust.
If this opportunity resonates with you, we encourage you to apply, even if you don't meet every requirement. This could be a pivotal career moment for you.
This role is fully remote, and we are currently seeking candidates located in USA time zones only.
Senior Analytics Engineer
The Opportunity:
The Senior Analytics Engineer plays a vital role in enabling our analysts and data-driven stakeholders by taking ownership of the architecture and infrastructure for data ingestion, transformation, testing, documentation, and connectivity throughout Grafana Labs. Effective communication with stakeholders is essential to develop a flexible data stack that accommodates our growing business needs.
What You’ll Be Doing:
- Manage and maintain the architecture and infrastructure of our data stack (e.g., BigQuery, dbt, Fivetran).
- Ensure the availability, accuracy, and accessibility of critical data for our stakeholders.
- Collaborate with GTM, Self-Serve, Marketing, Finance, BizApps, and other teams to assess their data needs and identify opportunities for enhancement within our analytics framework.
- Become the primary expert on our data systems.

