Analytics Engineer

Analytics Engineer Industrial Electric Manufacturing - 3.2 Jacksonville, FL Job Details $140,000 - $170,000 a year 15 hours ago Qualifications Data model design Stakeholder engagement Data visualization software proficiency Data Integration (Data management) Software coding Git SQL Continuous integration YAML Software documentation AI Cross-functional collaboration Python Cross-functional communication Dimensional modeling Stakeholder management Full Job Description At IEM, we're not just building innovative electrical distribution systems, we're shaping the future. IEM is dedicated to delivering world-class solutions for complex power needs. After 75 years, we continue to push the boundaries of what's possible. Whether you're an experienced professional or just starting out, you'll have the opportunity to contribute, grow, and make a lasting impact on industries that power the world's most dynamic markets.

Location:

US Remote Reports To:

Director of Data and Analytics Salary Range:

$140,000-$170,000

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:

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. 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 Dimensional Modeling:

Build conformed dimensions, fact tables, and reporting models that balance performance, maintainability, and business user accessibility for Tableau dashboards and ad-hoc analysis

Data Quality:

Author and maintain dbt tests, monitor freshness, investigate data quality issues end-to-end, and own resolution through to root cause

Business Partnership:

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.

Semantic Consistency:

Establish and document standardized metric definitions and reusable data models to ensure consistency, accuracy, and alignment across all reporting.

Documentation:

Maintain clear model descriptions, column-level documentation, and lineage notes that the team and downstream BI developers actually use

Engineering Standards:

Participate in code reviews, follow Git workflows and CI/CD practices, and contribute to evolving the team's modeling conventions and deployment standards

Source Integration:

Partner with the data engineering function on Fivetran and custom ingestion to ensure raw data lands in shapes that downstream models can rely on

BI Enablement:

Collaborate with BI developers and analysts to structure datasets for optimal Tableau performance and effective self-service analytics.

AI-Assisted Development:

Use AI coding assistants and agent-based tools to accelerate model development, test generation, refactoring, and documentation. Manage AI agents as part of your daily workflow to increase throughput and quality

Continuous Learning:

Stay current with the modern data stack and analytics engineering practices, bringing ideas back to the team and helping raise the bar over time

Qualifications:

Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related field (or equivalent experience), with 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 Preferred Qualifications Experience with manufacturing, construction, or project-based systems (e.g., Procore, ERP platforms like Infor, SAP, Oracle) Familiarity with semantic layers, metrics frameworks, or data cataloging and lineage tools Location Fully remote within the United States. May require up to 10% travel to IEM facilities for team collaboration, project kickoffs, and stakeholder meetings. Why Join IEM At IEM, you'll join a team that powers some of the world's most ambitious projects. We're engineers, makers, and problem-solvers who thrive on tackling complex challenges and delivering solutions that keep industries moving forward. If you're driven, collaborative, and ready to make an impact, we'd love to hear from you. Your creativity and passion can help us achieve great things—come be part of the journey. Learn more about IEM at https://www.iemfg.com We offer comprehensive and competitive benefits package designed to support our employees' well-being, growth, and long-term success. View a snapshot of our benefits at https://www.iemfg.com/careers Recruiting Scams Beware of recruiting scams. IEM never charges candidates fees, and all recruiter emails come from an @iemfg.com address. If you suspect fraudulent activity, do not share personal information and report it to us at iemfg.com/contact Non-Discrimination Statement IEM does not discriminate against any applicant based on any characteristic protected by law. Privacy Information collected and processed as part of your IEM Careers profile, and any job applications you choose to submit is subject to IEM's Workforce Member Privacy Policy.