WHAT YOU’LL DO  As a 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.  In this role you will:  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 WHO YOU ARE  Bachelor’s Degree  5 years of experience working in data engineering or architecture role Expertise in SQL and data analysis and experience with at least one programming language Experience developing and maintaining data warehouses in big data solutions  Big Data development experience using some or all of the following: 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  WHAT’S NICE TO HAVE  Bachelor’s degree in Computer Science, MIS, or Engineering  7+ years applicable work experience Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space  Experience in Python or Scala  Big Data development experience using Hive, Impala, Spark and familiarity with Kafka  Familiarity with the Linux operating system   Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics Experience with OLAP such as AtScale, SSAS, SAP BW, Essbase Knowledge of Data Preparation, Data Wrangling, and Feature Engineering