About the RoleWe are a fast-paced, high-growth company with a strong data analytics foundation - and we're looking for a Data Engineer to own, grow, and elevate our capabilities. You'll take the lead on backend infrastructure and dimensional data modeling for our internal BI dashboards and reporting, working directly with business stakeholders to turn requirements into impactful technical solutions. Just as importantly, you'll help position our data foundation for the next wave of AI use cases - from enabling natural language query, so stakeholders can ask questions of our data in plain English, to building the clean, well-modeled, and well-governed data layer that modern AI and LLM tooling depend on.
What You'll Own- Design, build, and maintain backend infrastructure and dimensional data models that power internal BI dashboards and reports.
- Own the development and ongoing maintenance of BI dashboards used by senior leadership and the board of directors, ensuring accuracy, clarity, and timely delivery of key business metrics.
- Drive ongoing enhancements to our data analytics reporting, including new data models, dashboards, and visualizations - and AI-powered, natural language query experiences that let business users self-serve answers.
- Lead the integration and ingestion of new data sources, expanding the breadth and depth of our analytics capabilities.
- Help prepare our data infrastructure for AI use cases - establishing the governed, well-modeled semantic layer and metadata that allow natural language query and AI-assisted analytics to run reliably on top of our data.
- Evaluate and operationalize AI capabilities within our existing stack (e.g., Snowflake Cortex and LLM functions) for high-value use cases such as automated metric commentary, anomaly detection in financial data, and extracting structured data from unstructured documents.
- Partner with business stakeholders to gather requirements and translate them into scalable, well-documented technical implementations.
- Act as the internal leader for data analytics infrastructure - identifying opportunities to improve performance, reliability, and coverage.
What We're Looking For- 3+ years of experience in data engineering, data analytics, or data science.
- Strong expertise with Snowflake, including data warehouse architecture and optimization.
- Advanced SQL proficiency, including complex queries, performance tuning, and data modeling.
- Solid understanding of dimensional data modeling concepts (star/snowflake schemas, facts, and dimensions).
- Experience with BI tools and dashboard development (e.g., Sigma, Tableau, Looker, Power BI, or similar).
- Proven ability to work cross-functionally - translating business requirements into reliable, scalable data solutions.
- Self-starter mentality with a desire to take ownership and grow within a high-impact role.
Nice to Have- Experience with Netsuite or similar ERP systems
- Experience with data pipeline tools such as dbt, Fivetran, Airflow, or similar.
- Proficiency in Python or another scripting language for data transformation and automation.
- Background in data science or analytics with exposure to statistical modeling or reporting.
- Hands-on experience applying AI on a data platform - e.g., Snowflake Cortex, LLM functions, vector embeddings, or building semantic models that power natural language query (Cortex Analyst, dbt Semantic Layer, or similar).
- Exposure to preparing data for ML/AI workflows, such as feature engineering, building model-ready datasets, or retrieval-augmented generation (RAG) pipelines.
