Staff Business Intelligence Data Analyst

Jamf

5h•$115,000 - $178,000•Remote

About The Position

The Staff Business Intelligence 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.

Requirements

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.
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.
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.
Demonstrated ownership of large, complex, cross-functional analytics projects from scoping through delivery.
Experience with data access and security practices both within and outside of a data warehouse.
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.
Strong analytical and problem-solving skills paired with a strategic mindset that cuts through ambiguity and connects analytical work to broader company objectives.
Ownership and autonomy: identifies gaps, drives work to completion at a high quality bar, and grows data capability across the team through mentoring.
Bachelor's degree in science, engineering, technology, mathematics, a related field, or an equivalent combination of relevant education and experience.

Nice To Haves

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.
Relevant certifications in data, analytics, or cloud platforms (e.g., dbt, Snowflake, or a major cloud provider) a plus.

Responsibilities

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.