Data Engineer III

The anticipated base pay compensation range for this position is $104,500.00 - $174,200.00. This role is eligible for an incentive target of up to 10 % or $ , based on the achievement of individual and company performance objectives in accordance with the current terms of the incentive program which are subject to change.

This position is not eligible for any form of sponsorship now or in the future. Individuals requiring sponsorship (e.g. OPT or H1B visa status) should not apply.

Only individuals authorized to work in the United States now and for the foreseeable future will be considered for this position.

Grainger is seeking a Data Engineer III to join our Machine Learning Engineering (MLE) team supporting Supply Chain and Inventory Analytics. This role reports to a Senior Manager of Machine Learning Engineering and partners closely with Inventory Reporting & Analysis (R&A). The objective of this role is to deliver high-quality, trusted, and scalable data pipelines that power advanced analytics, optimization, and machine learning.

This role will own the data foundation behind ML and analytics use cases, enabling faster decision-making, improving data reliability, and unlocking scalable insights across the business. This position is Hybrid requiring 2 days per week onsite at the Chicago or Lake Forest, IL offices.

- Pioneer a new way of thinking about Data Pipelines, Orchestration and Configuration at Grainger.

- Develop our next-generation micro-services to enhance and mature a data-driven culture

- Help develop the Analytics and Data Kubernetes products in AWS

- Experience building data products for Data Science use cases

- Identify and design internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes

- Build required tools for extraction, transformation and loading of data from data sources

- Work with partners including data, design, product and executive teams and assisting them with data-related technical issues

- 3+ years hands-on experience with Modern Data Engineering projects and practices (Airflow, Kafka, Spark, and python) required.

- Successful track record in developing and automating large-scale, high-performance data engineering systems (batch and streaming).

- Experience with both scripting and system programming languages (Python and Scala).

- Experience with microservices including defining and testing APIs

- Experience architecting, developing, and deploying both offline and online feature stores.

- Experience leading data integration efforts of data sources.

- Experience partnering with internal departments (Supply Chain, Marketing, Finance, and HR) to establish requirements.

- Develop junior team members through modern cloud-based development.

- Translate requirements into technical requirements and produce required source-to-target data mappings.

- Bring complex concepts into our organization and mentor others.

- Technology Experience Required: AWS, SQL, Python, Docker/Kubernetes, CI/CD, Git, Snowflake, dbt, Airflow.