Job Description

Description & Requirements

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 Kraft Heinz to advance data-driven decision-making capabilities across the enterprise. You will have a deep understanding of data architecture, data engineering, data analysis, and reporting -- and a basic understanding of data science techniques and workflows, as well as the business processes supported by the data pipeline. Examples of problems you will tackle include helping R&D determine the next generation of household products, revolutionizing consumer engagement with personally relevant content, and reinventing our supply chain to eliminate food waste. Furthermore, 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 Business Intelligence Engineers, Business Analyst 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 the evaluation, implementation and deployment of emerging tools and process for analytic data engineering in order to improve our productivity as a team
Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes
Partner with machine learning engineers, business intelligence engineers 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 required; Computer Science, MIS, or Engineering preferred
Expertise in ETL and data analysis and experience with SQL and at least one programming language (Python/R preferred)
Experience developing and maintaining data warehouses in big data solutions e.g. Snowflake
Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space (preferred)
Database development experience using Hadoop, SPARK or BigQuery and experience with a variety of relational, NoSQL, and cloud database technologies
Worked with BI tools such as Alteryx, Tableau, Power BI, Looker
Conceptual knowledge of data and analytics, such as dimensional modeling, ELT, reporting tools, data governance, data warehousing, structured and unstructured data.
Big Data Development experience using Hive, Impala, Spark and familiarity with Kafka (Preferred)
Familiarity with the Linux operating system
Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
An agile learner who brings strong problem-solving skills, and enjoys working as part of a technical, cross functional team to solve complex data problems
A hard worker and consensus gainer who brings a strong numbers sense; you are intellectually curious and willing to adjust your position based on additional information