Analytics Engineer

📋 Description

• The Analytics Engineer plays a pivotal role within IEM's modern data architecture, transforming raw source data into clean, well-structured datasets that are ready for business use, fueling Tableau dashboards, executive decisions, and self-service analytics across Finance, Production, Supply Chain, and Engineering.

• Primarily utilizing dbt and Snowflake, you will take ownership of the transformation layer that exists between data ingestion and the Business Intelligence surface: this includes staging models, intermediate logic, dimensional models, testing, and documentation.

• This role is a hands-on individual contributor position, granting you true ownership of production data models and a clear trajectory towards senior and principal analytics engineering as the team expands.

• Collaborate with cross-functional stakeholders and the Business Intelligence team (including Finance, Production, Supply Chain, and Engineering) to convert operational requirements into scalable data models and dependable metrics.

• Create and maintain dbt tests, monitor data freshness, investigate data quality issues from end to end, and take ownership of resolution down to the root cause.

• Design, construct, test, and document dbt models that transform raw Snowflake data into clean, reliable, analytics-ready datasets for Finance, Production, Supply Chain, and Engineering.

• Develop conformed dimensions, fact tables, and reporting models that strike a balance between performance, maintainability, and accessibility for business users engaging with Tableau dashboards and ad-hoc analysis.

⛳️ Requirements

• A 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, with a proven track record of owning production data models.

• Proficient SQL skills with experience in data transformation, complex querying, and performance optimization on large datasets.

• Practical experience with dbt, including incremental models, tests, macros, snapshots, and documentation.

• Familiarity with Snowflake or a similar cloud data warehouse, along with experience using ELT tools (e.g., Fivetran).

• A solid understanding of dimensional modeling concepts (including grain, surrogate keys, slowly changing dimensions, and star schemas).

• Working knowledge of Python for data processing, scripting, or lightweight integrations.

• Familiarity with Tableau or similar BI tools, and an understanding of how data structure influences performance.

• Experience with Git and modern development practices, which include code reviews and CI/CD workflows.

• Excellent communication skills, capable of translating technical concepts for business stakeholders and effectively gathering requirements.

• A collaborative team player who is open to training, mentoring, and engaging closely with non-technical stakeholders.

• Self-motivated and capable of working independently while collaborating with distributed teams.

• Experience utilizing AI coding assistants (e.g., Copilot, Claude) to aid in analytics engineering tasks such as SQL development, dbt modeling, testing, and documentation.

🏝️ Benefits

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