Staff Data Analyst

Jamf

5d•$115,000 - $178,000•Remote

About The Position

The Staff Data Analyst is a senior individual contributor who owns complex, cross-functional analytical initiatives from end to end and helps shape executive-level decisions. The role sets technical standards for the analytics team, including metrics frameworks, data modeling practices, and governance standards. It also serves as a trusted advisor to senior business stakeholders and contributes to Jamf’s AI-enabled analytics strategy. The analyst leads strategic analytical roadmaps and initiatives, partners with leadership and functional teams across Sales, Marketing, Finance, and Operations, and translates business questions into scalable data products and decision-shaping insights. The role establishes best practices in data modeling, storytelling, and analytics engineering; leads the design of scalable data infrastructure and workflows; and promotes data literacy across the organization. The position also contributes to roadmap and vision planning with Business Intelligence leadership, mentors analysts, and owns data quality and governance, including stewardship practices, data catalog maintenance, and the trustworthiness and discoverability of Jamf’s data assets.

Requirements

At least 8 years of experience in data as an analyst, engineer, or scientist.
At least 6 years working with large-scale (1B+ row) cloud data warehouses.
At least 6 years using business intelligence tools such as Tableau, Looker, Power BI, or DOMO.
Expert-level SQL.
At least 4 years building data models within a modern data stack such as dbt or Snowflake, including layered modeling, testing, performance optimization, and cost management.
Strong analytics engineering and data system design across databases, schemas, marts, aggregates, and views.
At least 4 years extending and maintaining a data model system for 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 inside and outside a data warehouse.
Excellent written and verbal communication and the ability to influence and build consensus across functional teams, including without direct authority.
Strong analytical and problem-solving skills, a strategic mindset, and the ability to connect analytical work to broader company objectives.
Ownership and autonomy: identify gaps, drive work to completion at a high quality bar, and grow team data capability through mentoring.
Bachelor’s degree in science, engineering, technology, mathematics, or 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 and achieving 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, such as dbt, Snowflake, or a major cloud provider.

Responsibilities

Lead analytical roadmaps and initiatives aligned with Jamf’s long-term goals; identify high-impact opportunities, address ambiguity, and represent the data function in leadership forums.
Own complex, cross-functional analytical projects from scoping and stakeholder alignment through delivery.
Advise senior leadership and analysts across Sales, Marketing, Finance, and Operations; translate business questions into scalable data products and insights that shape decisions.
Set standards for metrics definition, data modeling, data storytelling, and analytical best practices.
Lead the design of scalable data infrastructure and workflows using tools such as dbt, maintaining high standards for code quality and system design.
Lead cross-departmental initiatives to grow data literacy, including creating enablement resources, running training sessions, and embedding data-driven thinking into team practices.
Contribute to roadmap and vision planning with Business Intelligence leadership.
Mentor analysts at all levels and foster autonomy, constructive feedback, and continuous learning.
Own data quality and governance by improving the health, integrity, and discoverability of data assets, leading stewardship practices, maintaining the data catalog, and ensuring organizational trust in data.