Staff Analytics Engineer

At N-able, we’re not just helping businesses be secure —we’re redefining what it means to be cyber resilient. Our end-to-end platform blends AI-powered capabilities and flexible tech stacks, so customers can manage, secure, and recover with confidence. But the real power behind it all? Our people. We’re a global crew of N-ablites, who love solving complex problems, sharing knowledge, and delivering solutions that actually make a difference. If you're into meaningful work, fast growth, and a team that’s got your back, you’ll be surrounded by people who believe in what they do—and in you. We are looking to hire a senior, hands-on analytics engineer who can bring a strong blend of Snowflake, semantic modelling, SQL, Python and applied AI/LLM experience. We are looking for someone who can do more than traditional BI or data engineering: someone who can build the governed semantic layer that sits behind AI-driven analytics, understand how to evaluate and improve LLM outputs, and turn that foundation into scalable, reusable data products and interactive applications. You need to be technically strong but also comfortable working across BI, data engineering and governance teams, helping analysts adopt and maintain the models rather than becoming a single point of dependency.

- Hands-on Snowflake experience, ideally including Cortex Analyst, Cortex Agents, and Cortex Search, or comparable text-to-SQL and RAG systems, and a working grasp of why grounding LLMs in governed semantics beats pointing them at raw schema. - Strong Python and analytics-engineering fundamentals across Snowflake dynamic tables, streams, tasks, Snowpark, Git workflows, CI/CD, and automated testing, with the discipline to ship documented, maintainable, reviewable code. - Fluency with AI-assisted coding (Snowflake Cortex Code, Claude Code, or similar) as a daily driver for delivery; spec-driven development experience is a plus.

- Ideally 8 to 12 years in Business analytics and data engineering, with at least 1 year building semantic models or LLM-grounded analytics, and a track record of shipping data products that other teams reuse. - Deep SQL and dimensional/semantic modeling expertise (facts, dimensions, metrics, conformed entities), with hands-on experience building a semantic layer in Snowflake Semantic Views, dbt Semantic Layer, LookML, or similar. - Hands-on Snowflake experience, ideally including Cortex Analyst, Cortex Agents, and Cortex Search, or comparable text-to-SQL and RAG systems, and a working grasp of why grounding LLMs in governed semantics beats pointing them at raw schema.

- Deep SQL and dimensional/semantic modeling expertise (facts, dimensions, metrics, conformed entities), with hands-on experience building a semantic layer in Snowflake Semantic Views, dbt Semantic Layer, LookML, or similar. - Hands-on Snowflake experience, ideally including Cortex Analyst, Cortex Agents, and Cortex Search, or comparable text-to-SQL and RAG systems, and a working grasp of why grounding LLMs in governed semantics beats pointing them at raw schema. - Strong Python and analytics-engineering fundamentals across Snowflake dynamic tables, streams, tasks, Snowpark, Git workflows, CI/CD, and automated testing, with the discipline to ship documented, maintainable, reviewable code.

- Curate a verified query repository and custom instructions that raise answer accuracy over time. - Ship dynamic Streamlit apps 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. - Crosstrain BI analysts in each domain to tune, extend and maintain their domain models, building the hub-and-spoke that scales this beyond a single team.

- Proven experience evaluating LLM applications in production: test datasets, LLM-as-a-judge or programmatic scoring and using the results to drive iteration. Familiarity with Monte Carlo or similar data observability platforms is a plus. - Experience building dynamic, interactive data apps (Streamlit or similar) on top of a semantic layer, plus enough Tableau and Power BI to migrate what matters and modernize the reporting estate. - Strong communication skills with a knack for cross-training peers, able to run working sessions with BI analysts, translate ambiguous business asks into precise, certified definitions, and help peers tune the model confidently.

What You'll Do - Design and build governed Snowflake Semantic Views (logical tables, relationships, facts, dimensions, metrics, synonyms) as the shared vocabulary AI agents use to answer business questions. - Stand up the 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.

- Strong Python and analytics-engineering fundamentals across Snowflake dynamic tables, streams, tasks, Snowpark, Git workflows, CI/CD, and automated testing, with the discipline to ship documented, maintainable, reviewable code. - Fluency with AI-assisted coding (Snowflake Cortex Code, Claude Code, or similar) as a daily driver for delivery; spec-driven development experience is a plus. - Proven experience evaluating LLM applications in production: test datasets, LLM-as-a-judge or programmatic scoring and using the results to drive iteration. Familiarity with Monte Carlo or similar data observability platforms is a plus.