Kraft Heinz Company
Sr Data Engineer
Kraft Heinz Company, Chicago, Illinois, United States, 60290
Overview:
The Sr. Data Engineer is responsible for designing, developing, optimizing, and maintaining data architecture and pipelines that adhere to ELT principles and business goals. Specific duties include:Duties:Solve complex data problems to deliver insights that help our business achieve their goals.Interact with Plant managers, team leads, and business at the manufacturing plant to understand and develop IT solutions to automate/solve data issues.Create data products for Business Intelligence Engineers, Business Analysts, and Data Scientist team members to improve their productivity at the plant.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 processes for analytic data engineering 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.Maintain understanding of DevOps processes for code deployment via CI/CD pipelines and code integrity.Requirements:Bachelor's degree in Engineering, Computer Science, MIS, or directly related field, and at least ten (10) years of experience in data engineering or a closely related role.Must have some experience with: (1) Hands-on experience in working with Python programming, DBT, and SQL complex queries for transformation, streamlining data pipelines, and building workflows to automate jobs. (2) Snowflake data modeling and ELT using Snowflake SQL, implementing best practices with data warehouse and ETL concepts. (3) Loading data from SAP HANA, SharePoint, shared drives, and UNIX file systems into Snowflake cloud using Azure ADF.Knowledge of Azure architecture and monitoring of Azure Data services, data science, statistics, and/or applied mathematics.Developing manufacturing tools (like Overfill, OEE, Quality, and Maintenance) and deployment tools in a production environment.Involved in client interaction about business requirements and coordinated with offshore teams to complete the requirements and ensure smooth deliverables without any business impact.Location(s)
Chicago/Aon Center
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The Sr. Data Engineer is responsible for designing, developing, optimizing, and maintaining data architecture and pipelines that adhere to ELT principles and business goals. Specific duties include:Duties:Solve complex data problems to deliver insights that help our business achieve their goals.Interact with Plant managers, team leads, and business at the manufacturing plant to understand and develop IT solutions to automate/solve data issues.Create data products for Business Intelligence Engineers, Business Analysts, and Data Scientist team members to improve their productivity at the plant.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 processes for analytic data engineering 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.Maintain understanding of DevOps processes for code deployment via CI/CD pipelines and code integrity.Requirements:Bachelor's degree in Engineering, Computer Science, MIS, or directly related field, and at least ten (10) years of experience in data engineering or a closely related role.Must have some experience with: (1) Hands-on experience in working with Python programming, DBT, and SQL complex queries for transformation, streamlining data pipelines, and building workflows to automate jobs. (2) Snowflake data modeling and ELT using Snowflake SQL, implementing best practices with data warehouse and ETL concepts. (3) Loading data from SAP HANA, SharePoint, shared drives, and UNIX file systems into Snowflake cloud using Azure ADF.Knowledge of Azure architecture and monitoring of Azure Data services, data science, statistics, and/or applied mathematics.Developing manufacturing tools (like Overfill, OEE, Quality, and Maintenance) and deployment tools in a production environment.Involved in client interaction about business requirements and coordinated with offshore teams to complete the requirements and ensure smooth deliverables without any business impact.Location(s)
Chicago/Aon Center
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