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