Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Grafana @ 4
SQL @ 6
Looker @ 6
Tableau @ 6
dbt @ 3
ETL @ 4
Data Science @ 6
Leadership @ 4
Communication @ 4
Data Analysis @ 4
Reporting @ 4
QA @ 4
LLM @ 4
NetSuite @ 3
Snowflake @ 4
Salesforce @ 3
Observability @ 4
AI @ 4
Data Visualization @ 6
Data Modeling @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Grafana Labs is the company behind the open observability cloud, founded on principles of open source, open standards, open ecosystems, and open culture. Grafana Cloud is a fully managed observability platform used by millions and thousands of customers. We are a 100% remote company with a global team.
Responsibilities
- Data Modeling & Architecture: Partner with distributed data teams to build, iterate, and optimize corporate data architecture. Develop reliable data models to define company-wide performance metrics and track them from raw source data to reporting layers.
- Dashboards & Reporting: Design, build, and maintain production-quality dashboards and scalable data products. Establish reliable, automated tooling that allows internal stakeholders to monitor key operating metrics in real-time.
- Advanced Analytics & Deep Dives: Build advanced analytical models to uncover deeper insights into customer behavior and macro trends, mapping operational opportunities to financial outcomes.
- Executive Storytelling: Synthesize complex data and analyses into structured narratives and actionable insights for senior leadership and executives.
- Enablement & Governance: Lead cross-functional projects to develop datasets, provide documentation, and enable finance and business teams to self-serve basic data needs.
- Operational Excellence: Manage urgent, ad-hoc data analysis requests and maintain rigorous QA support for core financial data.
Requirements
- Professional Experience: 5+ years of experience in corporate analytics, financial analytics, data science, or a directly related quantitative field. Experience in a fast-paced technology or SaaS business is highly preferred.
- SQL Mastery: 5+ years hands-on SQL experience; daily habit of writing complex, highly efficient queries to build production-ready data models.
- Data Visualization: 3+ years building user-focused, production-quality dashboards in tools like Looker, Tableau, Mode, or Sisense. Previous experience with Grafana visualization, or a strong desire to learn it, is a major plus.
- Data Stack & Architecture: Practical experience with data model development, building ETL processes, and working within modern data warehouses (e.g., BigQuery, Snowflake). Familiarity with dbt is highly desirable.
- Business Systems: Familiarity with NetSuite and Salesforce to understand how financial and operational data flows from source to reporting layers.
- Executive Communication: Exceptional communication skills with proven ability to translate complex analysis into structured narratives for senior management.
- Analytical Balance: Strong critical reasoning and financial modeling skills; understanding of common data-analysis pitfalls and core SaaS metrics (ARR, NDR, retention).
Bonus / Preferred
- Experience in high-growth SaaS, cloud, or open-source companies, particularly public company or IPO readiness contexts.
- Proven success working within globally distributed, remote-first organizations.
- Experience documenting datasets and optimizing tooling for Model Context Protocol (MCP) ingestion, or constructing AI skills/plugins for LLM-driven internal data discovery.
Compensation and Rewards
- United States base compensation range: $143,759 - $172,511 (actual compensation may vary based on level, experience, and skillset). All roles include Restricted Stock Units (RSUs).
Other Details & Benefits
- 100% remote company (this role is United States - Remote).
- In-person onboarding to learn about the company and processes.
- Global annual leave policy of 30 days per annum (with 3 days reserved for Grafana Shutdown Days). The company will comply with local legislation where applicable.
- Equal opportunity employer; may utilize AI tools to assist in recruitment while reviewing CVs manually.