Analytics Engineer

Role Overview

• 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.
• Partner with cross-functional stakeholders and the Business Intelligence team (Finance, Production, Supply Chain, Engineering) to translate operational needs into scalable data models and reliable metrics.
• Author and maintain dbt tests, monitor freshness, investigate data quality issues end-to-end, and own resolution through to root cause.
• 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.
• Build conformed dimensions, fact tables, and reporting models that balance performance, maintainability, and business user accessibility for Tableau dashboards and ad-hoc analysis.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related field (or equivalent experience)
• 4–6 years of experience in analytics engineering, data engineering, or BI development, including ownership of production data models
• Strong SQL skills with experience in data transformation, complex querying, and performance optimization on large datasets
• Hands-on experience with dbt, including incremental models, tests, macros, snapshots, and documentation
• Experience working with Snowflake or a comparable cloud data warehouse, along with familiarity with ELT tools (e.g., Fivetran)
• Solid understanding of dimensional modeling (grain, surrogate keys, slowly changing dimensions, star schemas)
• Working knowledge of Python for data processing, scripting, or lightweight integrations
• Familiarity with Tableau or similar BI tools, with an understanding of how data structure impacts performance
• Experience with Git and modern development practices, including code reviews and CI/CD workflows
• Strong communication skills, with the ability to translate technical concepts for business stakeholders and gather requirements effectively
• A collaborative team player who is open to training, mentoring, and working closely with non-technical stakeholders
• Self-motivated and able to work independently while collaborating across distributed teams
• Experience leveraging AI coding assistants (e.g., Copilot, Claude) to support analytics engineering tasks such as SQL development, dbt modeling, testing, and documentation.

Tech Stack

• Cloud
• Python
• SQL
• Tableau

Benefits

• Comprehensive and competitive benefits package designed to support our employees' well-being, growth, and long-term success.