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.

· 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.

· Build logging, monitoring, and lineage across the layer; partner with data engineering and governance team members on observability for upstream pipelines and data products.

· 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.

· Embed governance and data quality by default, partnering with the Data Governance team members to meet certification, stewardship, and CDE requirements.

· 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.