Senior Business Intelligence Analytics Engineer

Jamf

17h•$103,100 - $186,780•Remote

About The Position

The Senior BI Analytics Engineer is a core technical role in Jamf’s data organisation. You’ll own the design and delivery of trusted data models across the Jamf Data Platform, from source-aligned staging layers through to the business-facing marts and semantic views that power BI, financial reporting, and product analytics. This is an end-to-end role: you think in systems, not just queries. You’ll bridge the gap between raw data from backend services and the decisions Jamf needs to make faster, working closely with data engineers, analysts, data scientists, and business stakeholders to ensure data is accurate, well-defined, and genuinely useful. As AI-powered analytics becomes central to how Jamf operates, you’ll also play a key role in building the semantic foundation that enables natural language querying through tools like Snowflake Cortex Analyst. You’ll raise the bar on data quality, drive best practices across the discipline, and help make the Jamf Data Platform a genuine competitive asset. You may be required to work periodically at a Jamf office or collaborative work location with other Jamf employees in your area for certain events or moments that matter. We are only able to accept applications for those based in one of these locations.

Requirements

Minimum of 6 years in Data as an Analyst, Engineer, Scientist, or equivalent (Required)
Minimum of 2 years managing the same data model system over time, extending it to satisfy multiple general business use case. (Required)
Minimum of 4 years working with a large-scale (1B+ Rows) Data Warehouse, preferably in a cloud environment (Required)
Minimum of 3 years building and maintaining data models using dbt, with demonstrable experience across modelling layers, testing, and documentation (Required)
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, dbt Semantic Layer, or equivalent (Required)
Experience building data solutions that support NLP-based querying, such as Text-to-SQL pipelines or conversational analytics interfaces that operate over structured data (Required)
Ability to communicate complex ideas simply and convincingly
Ability to listen to stakeholder needs and finds way to deliver well integrated solutions that serve specific needs.
Participation in ongoing security training is mandatory
Established security protocols will be adhered to, sensitive data will be handled responsibly, and data protection practices are followed, including understanding relevant privacy regulations and reporting breaches
Acknowledging the Jamf Code of Conduct, where applicable security and privacy policies can be found, is a requirement of all roles at Jamf

Nice To Haves

Experienced in Scrum or Kanban (Preferred)
General knowledge of Apple products and SaaS business models (Preferred)
A Bachelor’s Degree in Science, Technology, Engineering, Mathematics, or a related field is one route, but equivalent experience will be considered
A combination of relevant experience and education may be considered

Responsibilities

Design and build robust downstream data models using the Trusted Data Development workflow, covering range of analytics and integration use cases.
Design and maintain Snowflake semantic views with rich metadata annotation, business definitions, entity relationships, and column-level descriptions, enabling reliable AI-driven and natural language querying via tools such as Snowflake Cortex Analyst.
Partner with Data Platform and AI Architecture teams to build solutions that bridge structured analytics with natural language interfaces, making Snowflake data reliably queryable by AI agents and business users.
Set and uphold engineering standards writing maintainable, high-scale SQL and dbt code, leading code reviews, and acting as the code owner and BI reviewer for specific schemas.
Champion data quality and trusted data models implementing testing frameworks, driving data profiling, and partnering cross-functionally to resolve quality issues at their source.
Own one or more business stakeholder relationships, translating requirements into well-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.
Drive Data Platform optimisation identifying opportunities to reduce cost and complexity, contributing to the Data Catalog, and leading prioritisation of data governance issues.
Upskill analysts and business partners through code pairing, training, and documentation scaling data acumen and enabling self-service analytics across the organisation.
Lead multiple analytics projects from beginning to operationalization