Data Engineer - 332427

Grainger Businesses•Lake Forest, IL

1d•$153,400 - $174,200•Remote

About The Position

W.W. Grainger, Inc., is a leading broad line distributor with operations primarily in North America, Japan and the United Kingdom. At Grainger, We Keep the World Working® by serving more than 4.5 million customers worldwide with products and solutions delivered through innovative technology and deep customer relationships. Known for its commitment to service and award-winning culture, the Company had 2024 revenue of $17.2 billion across its two business models. In the High-Touch Solutions segment, Grainger offers approximately 2 million maintenances, repair and operating (MRO) products and services, including technical support and inventory management. In the Endless Assortment segment, Zoro.com offers customers access to more than 14 million products, and MonotaRO.com offers more than 24 million products. For more information, visit www.grainger.com. Grainger Corporate Services LLC is seeking a Data Engineer in Lake Forest, IL with the following requirements: Master’s degree in Computer Science, Engineering, or related field plus 6 years of related experience. Prior experience must include: Design and maintain scalable ETL workflows and automate data transformations and orchestration using Airflow, DBT, Wherescape, and scripting languages including Python, SQL, and shell scripting, leveraging cloud services like AWS Lambda and S3; Architect and manage cloud-native data pipelines and containerized applications to ensure high availability and scalability, using AWS and Kubernetes and FastAPI for building lightweight data-focused applications and microservices; Automate infrastructure provisioning and streamline DevOps processes using infrastructure-as-code and CI/CD tools, using Terraform, GitHub Actions, and Bitbucket; Extract and process enterprise data from SAP systems using ABAP variants, custom logic, and file-based integrations, enabling downstream analytics in platforms like Snowflake and Databricks and work closely with SAP functional teams to align data extraction with business requirements; Build high-performance data ingestion and transformation pipelines for large-scale analytics and real-time data using kafka and Apache Spark on Databricks. 100% remote work allowed from anywhere in the U.S.

Requirements

Master’s degree in Computer Science, Engineering, or related field
6 years of related experience
Design and maintain scalable ETL workflows and automate data transformations and orchestration using Airflow, DBT, Wherescape, and scripting languages including Python, SQL, and shell scripting, leveraging cloud services like AWS Lambda and S3
Architect and manage cloud-native data pipelines and containerized applications to ensure high availability and scalability, using AWS and Kubernetes and FastAPI for building lightweight data-focused applications and microservices
Automate infrastructure provisioning and streamline DevOps processes using infrastructure-as-code and CI/CD tools, using Terraform, GitHub Actions, and Bitbucket
Extract and process enterprise data from SAP systems using ABAP variants, custom logic, and file-based integrations, enabling downstream analytics in platforms like Snowflake and Databricks and work closely with SAP functional teams to align data extraction with business requirements
Build high-performance data ingestion and transformation pipelines for large-scale analytics and real-time data using kafka and Apache Spark on Databricks

Responsibilities

Design and maintain scalable ETL workflows and automate data transformations and orchestration using Airflow, DBT, Wherescape, and scripting languages including Python, SQL, and shell scripting, leveraging cloud services like AWS Lambda and S3
Architect and manage cloud-native data pipelines and containerized applications to ensure high availability and scalability, using AWS and Kubernetes and FastAPI for building lightweight data-focused applications and microservices
Automate infrastructure provisioning and streamline DevOps processes using infrastructure-as-code and CI/CD tools, using Terraform, GitHub Actions, and Bitbucket
Extract and process enterprise data from SAP systems using ABAP variants, custom logic, and file-based integrations, enabling downstream analytics in platforms like Snowflake and Databricks and work closely with SAP functional teams to align data extraction with business requirements
Build high-performance data ingestion and transformation pipelines for large-scale analytics and real-time data using kafka and Apache Spark on Databricks