Senior Analytics Engineer

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LEMNIS

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤲 Charity

📚 Education

🌍 Social Impact

Charity • Education • Social Impact

LEMNIS is a public charity dedicated to expanding learning opportunities for young people by creating inclusive, community-connected learning environments. The organization partners with researchers and practitioners in neuroscience, social science, digital technology, and artificial intelligence to design experiences that foster belonging, connection, and lifelong growth. Lemnis works alongside changemakers and operates divisions such as Mainstay and InsideTrack to scale its impact; it is based in Beaverton, Oregon and notes it does not accept unsolicited grant proposals.

📋 Description

• Own and expand our semantic layer • Lead semantic layer development in dbt as the single source of truth for metrics across dashboards, reports, AI tools, and embedded analytics • Partner with the Senior Data Engineer on data architecture and quality testing for data products • Deprecate legacy reporting methods and drive adoption of the semantic layer as the default • Translate technical concepts and internal terminology into business language so data is intuitive for non-technical users • Build analytics products that drive business value • Lead refreshes and new builds of internal and partner-facing analytics products that help us identify risks and surface opportunities • Support embedded analytics work that brings customer-facing dashboards directly into the product • Partner with Partner Success, Product, and Leadership to gather requirements and design analytics products that answer the question behind the question • Make data trusted, accessible, and easy to use • Own our internal data knowledge base - the centralized source for documentation, metric definitions, and lineage • Create documentation, short-form videos, and dashboard guides that help employees use data confidently • Support cross-functional data power users for knowledge sharing and feedback on data products • Partner on data literacy training and onboarding, including new-hire modules and annual refreshers • Support our AI initiatives • Build and maintain the verified query repository and curated data assets that power our internal AI agents • Monitor agent performance and identify gaps in context or data that can be addressed at the data layer

🎯 Requirements

• 5+ years in analytics engineering, data analytics, or BI engineering, with at least 3 years owning data modeling end-to-end • Strong SQL and production experience with dbt (you've built, tested, and maintained models, not just tinkered) • Hands-on experience with a modern cloud warehouse (Snowflake, BigQuery, Databricks, or Redshift) • Experience with software engineering best practices (git, CI/CD, PRs) • Solid data modeling fundamentals - dimensional modeling, slowly-changing dimensions, OLTP vs OLAP, knowing when to materialize vs. view • Experience with a modern BI tool (Sigma, Looker, Hex, Tableau, Mode, or similar) • Excellent written communication - you can explain a metric to a VP and document it for a new hire in the same afternoon • Strong stakeholder management - you've worked directly with non-technical teams and helped them ask better questions • Comfort with ambiguity and a bias toward making things simpler. • Direct experience with semantic layers (dbt Semantic Layer, Cube, LookML) • Snowflake experience, especially with semantic views and Cortex • Familiarity with AI evals, prompt evaluation, or working alongside ML/AI initiatives • EdTech, higher education, or B2B SaaS background • Experience building documentation systems or running data enablement programs • Python proficiency for modeling and analysis work