Machine Learning/Data Engineer

General Mills
General Mills

Job Overview

Machine Learning/Data Engineer

Job LocationsUS-MN-Minneapolis

Requisition ID



Digital & Technology, Global Security, or Global Shared Services

Company Overview

Were passionate about food and driven by data.
Do you want to impact our future through data, analytics and innovative technology? Do you thrive on leading big things and making it happen? Bring your passion, expertise and problem-solving skills to the table and make an impact.

General Mills is reshaping the future, and technology & data play an important role for us. Your technology experience will help us get the right data and solutions at the right time, every time. As one of the worlds leading food companies,
General Mills operates across the globe with more than 100 recognizable consumer brands, including: Cheerios, LRABAR, Pillsbury, Yoplait, Annies Homegrown, Totinos, Epic Provisions and Blue Buffalo.

Job Overview


As a Machine Learning / Data Engineer, you will work closely with a multidisciplinary agile team to build high quality data pipelines driving analytic solutions. These solutions will generate insights from our connected data, enabling General Mills to advance the data-driven decision-making capabilities of our enterprise. This role requires deep understanding of data architecture, data engineering, data analysis, reporting, and a basic understanding of data science techniques and workflows. This team is amid transitioning data engineers into machine learning engineers. In addition, we are moving from Hadoop to Google Cloud. In this role you will:

  • Increase the Teams ability to understand, train, and develop ML models and supporting data pipelines
  • Utilize machine learning models as APIs or software libraries to be integrated into a cloud application
  • Establish scalable, efficient, automated processes for large scale data analyses, model development, validation, and implementation.
  • Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals.
  • Solve complex data problems to deliver insights that helps our business to achieve their goals
  • Create data products for analytics and data scientist team members to improve their productivity
  • Advise, consult, mentor and coach other data and analytic professionals on data standards and practices
  • Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions
  • Lead evaluation, implementation and deployment of emerging tools & process for analytic data engineering to improve our productivity as a team
  • Develop and deliver communication & education plans on analytic data engineering capabilities, standards, and processes
  • Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
  • Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics



  • Bachelors Degree
  • Two (2+) or more years of professional experience in data engineering, software development/engineering, or data science
  • Two (2+) or more years of hands on development with frameworks such as Python, Java, Scala
  • Experience of developing, deploying, maintaining and debugging ML / Data Science models in a production environment
  • Expertise in SQL and data analysis and experience
  • Experience developing and maintaining data warehouses in big data solutions
  • Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
  • Big Data development experience using Hadoop, Hive, BigQuery, Impala, Spark and familiarity with Kafka
  • Experience working with BI tools such as Tableau, Power BI, Looker, Shiny
  • Conceptual knowledge of data and analytics, such as dimensional modeling, ETL, reporting tools, data governance, data warehousing, structured and unstructured data.
  • Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
  • Passion for agile software processes, data-driven development, reliability, and experimentation
  • Experience working on a collaborative agile product team
  • Excellent communication, listening, and influencing skills


  • Bachelors degree in Computer Science, MIS, or Engineering
  • 5+ years applicable work experience
  • Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space
  • Familiarity with the Linux operating system
  • Experience with OLAP such as AtScale, SSAS, SAP BW, Essbase
  • Knowledge of Data Preparation, Data Wrangling, and Feature Engineering
  • Experience work with Googles cloud data ecosystem
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