At Jamf, we believe in an open, flexible culture based on respect and trust. Our track record and thriving work environment all stem from the freedom we grant ourselves to get the job done right. We take pride in helping tens of thousands of customers around the globe succeed with Apple.

The secret to our success lies in our connectivity, while operating with a high degree of flexibility. Work-life balance remains our priority while feeling connected is important to maintain our strong culture, achieve our goals, and thrive as #OneJamf.

What you'll do at Jamf

The Staff Data Analyst is a senior individual contributor who takes end-to-end ownership of complex, cross-functional analytical initiatives that shape decisions at the executive level. This role sets the standard for technical excellence across the analytics team, defining metrics frameworks, data modeling practices, and governance standards while serving as a trusted advisor to senior business stakeholders and a key contributor to Jamf's AI-enabled analytics strategy.

What you can expect to do in this role

Drive strategic impact by leading analytical roadmaps and initiatives that align with Jamf's long-term goals. Identify high-impact opportunities, cut through ambiguity on critical initiatives, and represent the data function in leadership forums.
Take end-to-end ownership of complex, cross-functional analytical projects, from scoping and stakeholder alignment through to delivery.
Partner with senior leadership and functional analysts as a trusted analytical advisor across Sales, Marketing, Finance, and Operations, translating business questions into scalable data products and delivering insights that shape decisions.
Set the standard for metrics definition, data modeling, data storytelling, and analytical best practice across the team. Lead the design of scalable data infrastructure and workflows using tools such as dbt, and maintain a high bar for code quality and system design.
Lead cross-departmental initiatives that grow data literacy across Jamf, including developing enablement resources, running training sessions, and embedding data-driven thinking into how teams operate.
Contribute to roadmap and vision planning alongside Business Intelligence leadership.
Mentor analysts at all levels, accelerating their technical and business growth, and foster a culture of autonomy, constructive feedback, and continuous learning.
Own data quality and governance by driving the health, integrity, and discoverability of Jamf's data assets, leading stewardship practices, maintaining the data catalog, and ensuring data is trusted across the organization.

What we are looking for

8+ years in data as an analyst, engineer, or scientist, including 6+ years working with large-scale (1B+ row) cloud data warehouses and 6+ years using business intelligence tools such as Tableau, Looker, Power BI, or DOMO. (Required)
Expert-level SQL and 4+ years building data models within a modern data stack (dbt, Snowflake, or equivalent), including layered modeling, testing, performance optimization, and cost management. (Required)
Strong analytics engineering and data system design across databases, schemas, marts, aggregates, and views, including 4+ years extending and maintaining a data model system to serve multiple business use cases, with the ability to architect scalable, future-proofed solutions and set technical direction for a team. (Required)
Demonstrated ownership of large, complex, cross-functional analytics projects from scoping through delivery. (Required)
Experience with data access and security practices both within and outside of a data warehouse. (Required)

PREFERRED

Experience building multi-quarter analytical roadmaps or leading organization-wide data initiatives.
Experience introducing a new tool, technique, or pattern to a team, with measurable productivity or quality improvements.
Familiarity with SaaS business metrics such as ARR, churn, retention, NRR, and product usage analytics.

CORE COMPETENCIES

Excellent written and verbal communication, with the ability to influence and build consensus across functional teams, including without direct authority, from a data model review to an executive presentation.