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N-able

IT management suite for MSPs

Staff Analytics Engineer

Business IntelligenceConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Ideally have 8 to 12 years of experience in business analytics and data engineering, including at least 1 year building semantic models or LLM-grounded analytics, and a track record of shipping reusable data products.
  • Have deep SQL and dimensional/semantic modeling expertise, including facts, dimensions, metrics, and conformed entities, with hands-on experience building a semantic layer in Snowflake Semantic Views, dbt Semantic Layer, LookML, or similar.
  • Have hands-on Snowflake experience, ideally including Cortex Analyst, Cortex Agents, and Cortex Search, or comparable text-to-SQL and retrieval-augmented generation systems, and understand the value of grounding large language models in governed semantics rather than raw schemas.
  • Have strong Python and analytics-engineering fundamentals across Snowflake dynamic tables, streams, tasks, Snowpark, Git workflows, continuous integration and delivery, and automated testing; ship documented, maintainable, reviewable code.
  • Use AI-assisted coding tools such as Snowflake Cortex Code or Claude Code for daily delivery; spec-driven development experience is a plus.
  • Have proven experience evaluating production LLM applications using test datasets, LLM-as-a-judge or programmatic scoring, and results-driven iteration. Familiarity with Monte Carlo or similar data observability platforms is a plus.
  • Have experience building dynamic, interactive data applications with Streamlit or similar on top of a semantic layer, plus enough Tableau and Power BI experience to migrate relevant dashboards and modernize reporting.
  • Be able to run working sessions with BI analysts, translate ambiguous business requests into precise, certified definitions, and help peers tune models confidently.

Responsibilities

  • Design and build governed Snowflake Semantic Views, including logical tables, relationships, facts, dimensions, metrics, and synonyms, as the shared vocabulary AI agents use to answer business questions.
  • Build an evaluation harness for the semantic and agentic layer, including golden-question datasets, LLM-as-a-judge scoring, and side-by-side runs that gate every release.
  • Build logging, monitoring, and lineage across the layer; partner with data engineering and governance teams on observability for upstream pipelines and data products.
  • Curate a verified query repository and custom instructions to improve answer accuracy over time.
  • Ship dynamic Streamlit applications and lightweight data products on top of the semantic layer using AI-assisted coding, modernizing legacy Tableau and Power BI dashboards into faster, interactive experiences.
  • Cross-train BI analysts in each domain to tune, extend, and maintain their domain models, building a hub-and-spoke approach that scales beyond a single team.
  • Embed governance and data quality by default, partnering with the Data Governance team to meet certification, stewardship, and CDE requirements.

Desired Qualifications

  • Familiarity with Monte Carlo or similar data observability platforms.
  • Spec-driven development experience.

About the Company

N-able

IT management suite for MSPs

N-able provides a suite of IT management tools designed for Managed Service Providers (MSPs). It offers remote support, AI- and ML-powered endpoint detection and response, and cloud-first backup solutions to streamline IT service management, improve security, and boost efficiency. The products are cloud-based and offered on a subscription model, emphasizing ease of use, integration with other tools, and affordability to serve a wide range of MSP customers. The company differentiates itself by focusing specifically on MSP workflows, providing essential tools without unnecessary complexity, and offering extensive training and support resources to help MSPs succeed. Its overall goal is to help MSPs protect their clients’ data, manage IT environments efficiently, and deliver reliable, high-quality service.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Ottawa, Canada
Founded
2000

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