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# Analytics and Intelligence Engineer

- **Company:** Mars
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $119,040.0 - $163,680.0
- **Contract:** Permanent contract
- **Skills:** Adaptable Database Systems, Airflow, Business Analytics Applications, Data Analysis, Automation of Tests, Code Review, Information Systems, Continuous Integration, Data Transformation, Python (Programming Language), Power BI, SQL Databases, Tableau (Software), Workflow Management Systems, Azure Data Factory, Snowflake, Git, Data Layers, Git Flow, Information Technology, Code Testing, Data Analytics, Tools for Reporting, Software Version Control, Databricks
- **Published:** October 28, 2026
- **Apply:** https://www.jofdav.com/jobs/60314852-analytics-and-intelligence-engineer

## About the Role

An Analytical Problem Solver: You enjoy untangling complex data challenges, exploring patterns, and translating business questions into reliable analytical models.
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A Team Player & Collaborator: You thrive working within an agile team of engineers, sharing knowledge openly, giving and receiving constructive code reviews, and learning from peers.
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Quality & Automation-Focused: You take pride in writing clean, well-tested code and automating repetitive workflows.
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Curious & Adaptable: You stay curious about new tools, approaches, and CPG trends, adapting comfortably as business needs evolve.

Qualifications & Experience
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3-6+ years of hands-on experience in analytics engineering, business intelligence, or data analytics, delivering reliable data models and production dashboards.
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Education: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems, Business Analytics, or related field (or equivalent practical experience)., + Strong proficiency in SQL; experience building and optimizing dimensional models (Star Schemas) and analytical tables.

 + Practical experience with modern data transformation and lakehouse tools, such as dbt, Databricks, Snowflake, or Azure Data Services.
 + Hands-on experience developing intuitive, performant dashboards in platforms such as Power BI or Tableau.
 + Working knowledge of Python or R for exploratory analysis, data transformation, or automation.
 + Familiarity with Git workflows, pull requests, and automated testing frameworks (e.g., dbt test).
 + Exposure to data cataloguing/governance tools (e.g., Unity Catalog) and workflow orchestration (e.g., Databricks Workflows, Airflow, or Azure Data Factory).
 * Experience working within CPG, retail, DTC, or manufacturing environments is a plus.

## Description

* Partner with cross-functional business stakeholders and engineering peers to build consistent KPI dashboards, reliable data assets, and high-impact reporting tools.
 * Build, test, and maintain robust, scalable data models and semantic layers (using Star Schemas, dbt, and Databricks) that serve as a dependable single source of truth for the Mars Accelerator Division.
 * Collaborate with data scientists and analytics peers to incorporate predictive models, statistical forecasting algorithms, and anomaly detection into business-facing dashboards and semantic layers.
 * Actively follow modern software engineering best practices for data, including version control with Git, collaborative code reviews, automated testing (e.g., dbt tests, data quality validation), and continuous integration (CI/CD).
 * Create well-documented, certified datasets and provide guidance and technical support to business users to help them self-serve data with confidence.
 * Maintain high standards for data accuracy, testing, and cataloguing (e.g., Databricks Unity Catalog) to ensure enterprise data remains governed, accessible, and compliant.
 * Act as a hands-on technical resource for BI platforms (e.g., Power BI, Tableau), developing performant, intuitive dashboards and participating in peer reviews to maintain high visual and performance standards.
 * Participate in agile planning, sprint execution, and backlog refinement, delivering well-scoped analytics solutions on time.