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Mars Snacking Analytics and Intelligence team is seeking an Analytics and Intelligence Engineer to design, develop, and enhance division reporting, semantic modelling, and intelligence capabilities. You will work with data scientists, engineers, and business stakeholders across sales, marketing, supply chain, and finance to build reliable data products and dashboards.
You will bridge business needs with robust data engineering practices, integrate predictive intelligence into workflows, and
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.
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).