Analytics and Intelligence Engineer

Job Description:

Accelerator, a global Division of Mars Snacking, is on the front line of unlocking growth across high-potential categories and brands to fuel what’s next for Snacking. It’s home to both emerging and enduring brands, including KIND, TRÜ FRÜ, NATURE’S BAKERY, RXBAR, EGGO, POP-TARTS and RICE KRISPIE TREATS. Combining the scale of Mars with the agility of a start-up, our Division has the ambition to accelerate the future of snacking by delivering products consumers love today, discovering category-shaping innovations for tomorrow and developing entrepreneurial teams whose impact will last for generations.

We’re looking for passionate talent who dare to dream big, agile collaborators who talk straight and decide fast, and driven performers with a growth mindset. We’re proudly part of Mars, while also building something boldly different. If this inspires and energizes you, you’ve found the right place where you can do cool things with fun people for one of the biggest snacking companies in the world!

As an Analytics and Intelligence Engineer, you will be a key member of our collaborative Data and Analytics team, contributing directly to the design, development, and enhancement of Mars Accelerator division reporting, semantic modelling, and intelligence capabilities. You will partner alongside fellow engineers, data scientists, and business stakeholders across sales, marketing, supply chain, and finance to turn complex business requirements into dependable analytical data models and actionable dashboards.

In this role, you will help bridge business needs with robust data engineering practices, building high-quality data products, integrating predictive and automated intelligence into analytical workflows, and contributing to the continuous improvement of our modern analytics stack.

What You’ll Do

• 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.

You Are…

• An Analytical Problem Solver: You enjoy untangling complex data challenges, exploring patterns, and translating business questions into reliable analytical models.

• 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.

• Quality & Automation-Focused: You take pride in writing clean, well-tested code and automating repetitive workflows.

• Curious & Adaptable: You stay curious about new tools, approaches, and CPG trends, adapting comfortably as business needs evolve.

Qualifications & Experience

• 3–6+ years of hands-on experience in analytics engineering, business intelligence, or data analytics, delivering reliable data models and production dashboards.

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems, Business Analytics, or related field (or equivalent practical experience).

• Core Technical Skills:

  • 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.

What can you expect from Mars?

• Work with diverse and talented Associates, all guided by the Five Principles.

• Join a purpose driven company, where we’re striving to build the world we want tomorrow, today.

• A strong focus on learning and development support from day one, including access to our in-house Mars University.

• An industry competitive salary and benefits package, including company bonus.

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The base pay range for this position at commencement of employment is between the range listed below, however, base pay offered may vary depending on multiple individualized factors, including but not limited to job-related knowledge, skills, and experience. The total compensation package for this position will include variable pay, medical and dental benefits, participation in 401k plan, and paid time off benefits. Details of participation in these benefit plans will be provided if an applicant receives an offer of employment.