Analytics Engineer
About the role
Position Summary
The Analytics Engineer sits at the heart of IEM's modern data stack, turning raw source data into the clean, well-modeled, business-ready datasets that power Tableau dashboards, executive decisions, and self-service analytics across Finance, Production, Supply Chain, and Engineering. Working primarily in dbt and Snowflake, you own the transformation layer between ingestion and the BI surface: staging models, intermediate logic, dimensional models, tests, and documentation. This is a hands-on individual contributor role with real ownership of production data models and a clear path into senior and principal analytics engineering as the team grows.
Key Responsibilities
- dbt Transformation Models: Design, build, test, and document dbt models that turn raw Snowflake data into clean, reliable, analytics-ready datasets across Finance, Production, Supply Chain, and Engineering
Ideal Candidate Profile
You have 4 to 6 years of experience building production analytics models in cloud environments, with strong dbt and SQL fundamentals and meaningful Snowflake exposure. You think in grain, keys, and tests before you think in dashboards. You write clean, documented, peer-reviewed code and pride yourself on the readability of your YAML. You partner naturally with business stakeholders, translating fuzzy operational questions into well-shaped datasets and surfacing the questions behind the questions. You are comfortable working alongside data engineers on ingestion, with BI developers on consumption, and with finance and operations leaders on definitions. You are excited about AI's role in modern analytics work and already use AI coding assistants and agents as a daily multiplier for SQL, dbt, testing, and documentation.