Senior Business Intelligence Analytics Engineer

Responsibilities

• Design and build robust downstream data models using the Trusted Data Development workflow to support a range of analytics and integration use cases.
• Author and maintain Snowflake semantic views with rich metadata, business definitions, entity relationships, and column descriptions to enable reliable AI-driven and natural language querying via tools like Snowflake Cortex Analyst.
• Collaborate with Data Platform and AI Architecture teams to create solutions that bridge structured analytics with natural language interfaces, ensuring Snowflake data is reliably queryable by AI agents and business users.
• Establish and uphold engineering standards for maintainable, high-scale SQL and dbt code; lead code reviews and act as code owner and BI reviewer for designated schemas.
• Champion data quality and trusted data models by implementing testing frameworks, driving data profiling, and working cross-functionally to resolve issues at their source.
• Own one or more business stakeholder relationships, translating requirements into integrated data designs and ensuring raw data is accurately interpreted across business units, drawing on depth in at least two major data domains such as marketing, sales, finance, product, or engineering.
• Identify opportunities to optimize the Data Platform to reduce cost and complexity, contribute to the Data Catalog, and lead the prioritization of data governance issues.
• Upskill analysts and business partners through code pairing, training, and scalable documentation to broaden data acumen and enable self-service analytics across the organization.
• Lead multiple analytics projects from inception to operational deployment.

Requirements

• Minimum of 6 years in data roles such as analyst, engineer, scientist, or equivalent.
• At least 2 years managing the same data model system over time, extending it to satisfy multiple general business use cases.
• Minimum of 4 years working with a large-scale data warehouse (1B+ rows), preferably in a cloud environment.
• Minimum of 3 years building and maintaining data models using dbt, with demonstrable experience across modeling layers, testing, and documentation.
• Experience developing semantic views or semantic layer data models designed for LLM or AI integrations, including metadata standards, business glossaries, and column-level descriptions that support reliable AI-driven querying, using tools such as Snowflake Cortex Analyst or dbt Semantic Layer.
• Experience building data solutions that support NLP-based querying, such as Text-to-SQL pipelines or conversational analytics interfaces over structured data.
• Education: Bachelor's Degree in Science, Technology, Engineering, Mathematics, or related field (or equivalent experience).

Technologies

• SQL
• dbt
• Snowflake Cortex Analyst
• Snowflake

Security and privacy requirements

• Participation in ongoing security training is mandatory.
• Adhere to established security protocols; handle sensitive data responsibly and follow data protection practices, including awareness of privacy regulations and breach reporting.
• Acknowledge Jamf Code of Conduct; applicable security and privacy policies are available and must be followed.

Pay Transparency

Salary range: USD 103,100 - 186,780 per year. Base pay is part of the total compensation package and varies by hiring location within defined ranges. Final offers depend on role scope, location, budget, skills, experience, and qualifications, with the aim of fair, competitive pay and growth opportunities as you develop in the role.

What it means to be a Jamf

We are a team of free thinkers, doers, and problem solvers who value humility and continuous learning. Our culture emphasizes selflessness and relentless improvement, fueling both personal growth and collective progress as we pursue shared goals while honoring individual approaches.

What Jamf does

Jamf extends the Apple experience from personal use to the workplace, enabling secure automation of deployment, management, and security for Mac, iPad, iPhone, and Apple TV across organizations—empowering customers to protect data and applications while enabling productive, secure work environments.