Senior Analytics Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership and enhance our semantic layer.

• Spearhead the development of the semantic layer in dbt, establishing it as the definitive source of truth for metrics utilized across dashboards, reports, AI tools, and embedded analytics.

• Collaborate with the Senior Data Engineer on data architecture and quality assurance for data products.

• Phase out outdated reporting methods and promote the adoption of the semantic layer as the standard.

• Convert technical concepts and internal jargon into business-friendly language, ensuring data is easily understood by non-technical users.

• Develop analytics products that deliver significant business value.

• Oversee updates and new creations of internal and partner-facing analytics products, aiding in the identification of risks and the uncovering of opportunities.

• Enhance embedded analytics efforts that integrate customer-facing dashboards directly into the product.

• Collaborate with Partner Success, Product, and Leadership teams to collect requirements and design analytics products that address underlying queries.

• Ensure data is reliable, accessible, and user-friendly.

• Manage our internal data knowledge base, serving as the centralized repository for documentation, metric definitions, and data lineage.

• Produce documentation, short-form videos, and dashboard guides that empower employees to utilize data with confidence.

• Assist cross-functional data power users with knowledge sharing and feedback on data products.

• Collaborate on data literacy training and onboarding, including modules for new hires and annual refreshers.

• Support our AI initiatives.

• Build and maintain a verified query repository and curated data assets that fuel our internal AI agents.

• Monitor agent performance and identify gaps in context or data that can be rectified at the data layer.

⛳️ Requirements

• 5+ years of experience in analytics engineering, data analytics, or BI engineering, with a minimum of 3 years managing data modeling from start to finish.

• Proficient in SQL with practical experience using dbt (you have built, tested, and maintained models, not just experimented).

• Hands-on experience with a modern cloud data warehouse (Snowflake, BigQuery, Databricks, or Redshift).

• Familiarity with software engineering best practices (git, CI/CD, PRs).

• Strong foundational knowledge in data modeling - including dimensional modeling, slowly-changing dimensions, OLTP vs OLAP, and understanding when to use materialized views vs. regular views.

• Experience with contemporary BI tools (Sigma, Looker, Hex, Tableau, Mode, or similar).

• Exceptional written communication skills - able to explain a metric to a VP and document it for a new hire within the same day.

• Strong stakeholder management abilities - you have directly collaborated with non-technical teams to help them formulate better questions.

• Comfortable with ambiguity and possess a tendency towards simplification.

• Direct experience with semantic layers (dbt Semantic Layer, Cube, LookML).

• Experience with Snowflake, particularly with semantic views and Cortex.

• Familiarity with AI evaluations, prompt assessment, or collaboration with ML/AI initiatives.

• Background in EdTech, higher education, or B2B SaaS.

• Experience in developing documentation systems or managing data enablement programs.

• Proficiency in Python for modeling and analytical tasks.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work opportunities.

• Professional development and training programs.

• Collaborative and innovative work environment.