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Grainger is seeking a Senior Data Engineer to design and operate scalable data pipelines and data products. The role focuses on batch and real-time data processing, leveraging Databricks, Snowflake, Spark, and Kubernetes on cloud platforms.
You will translate requirements into robust data solutions, improve data quality, and collaborate with engineering and product teams to enable analytics, ML, and AI-enabled experiences.
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Location: LAKE FOREST, IL, US, 60045-5202
Work Location Type: Hybrid
W.W. Grainger, Inc. is a leading broad line distributor with operations primarily in North America and Japan. At Grainger, We Keep the World Working®by serving more than4.6 million customersworldwide with maintenance, repair andoperating(MRO) products and value-added solutions delivered through innovative technology and deep customerexpertise. Known for its commitment to service and purpose-driven culture, the Company reported2025 revenue of$17.9 billion. For more information, visit www.grainger.com.
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.
With benefits starting on day one, our programs provide choice and flexibility to meet team members' individual needs, including:
For additional information and details regarding Grainger’s benefits, please click on the link below:
The pay range provided above is not a guarantee of compensation. The range reflects the potential base pay for this role at the time of this posting based on the job grade for this position. Individual base pay compensation will depend, in part, on factors such as geographic work location and relevant experience and skills.
The anticipated compensation range described above is subject to change and the compensation ultimately paid may be higher or lower than the range described above.
Grainger reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion at any time, consistent with applicable law.
Grainger's Product Discovery organization is investing in modern Data Engineering capabilities that support search platforms, search relevance, machine learning, analytics, and emerging AI-enabled experiences.
In this role, you will design and operate reliable, governed batch and real-time data products using technologies such as Databricks, Snowflake, Spark, Kubernetes, vector/search technologies and cloud-native services. You will build the pipelines, data assets, orchestration patterns, and search and retrieval capabilities that make trusted data available to search, machine learning, analytics, and engineering teams.
You will be responsible for designing, developing, and maintaining scalable data solutions that Integrate and transform data for business and analytical use. You will apply data engineering practices to deliver reliable, high‑quality data products and improve the performance, scalability, and automation of data processes. The Senior Data Engineer partners with technical and business stakeholders to translate requirements into effective data solutions.
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.
Design, develop, test, and maintain scalable data pipelines and data products that integrate information from
Build solutions to extract, transform, integrate, and deliver reliable data for analytical and business needs.
Develop and enhance data engineering capabilities that improve data accessibility, performance, quality, and scalability.
Analyze requirements and translate business and technical needs into data designs, specifications, and solutions.
Identify and implement improvements to data engineering processes, including automation, optimization, and increased reliability.
Partner with technical and business stakeholders to resolve data-related challenges and deliver solutions that meet business requirements.
Provide technical guidance, review designs, and help establish engineering practices for less-experienced team members.
Design and deliver scalable batch and streaming data pipelines and data products across modern data and cloud platforms.
Define reusable Data Engineering patterns for CDC, event-driven processing, workflow orchestration, data products, and AI/search-enabled workloads.
Partner with Engineering, Product, and Applied Science to shape architecture, roadmap, adoption, and operational ownership of data capabilities.
Bachelor's Degree or equivalent experience in Computer Science, Computer Engineering, Information Systems, Data Science, Software Engineering, or a closely related technical field or equivalent experience
3+ years' experience in related data engineering or software engineering experience
Experience building and operating production batch and streaming data pipelines on Databricks or similar modern data platforms.
Strong software engineering skills in Python with hands‑on experience using Spark or other distributed processing frameworks.
Hands‑on experience with CDC, streaming/event‑driven architectures, and workflow orchestration, with the ability to select appropriate patterns based on scale, reliability, and use case.
Experience with containerization and orchestration technologies such as Docker and Kubernetes, along with cloud platforms such as AWS or equivalent.
Experience implementing CI/CD and automated testing using platforms such as GitHub Actions or equivalent.
Experience working across relational, NoSQL, vector, graph, or other database technologies and selecting appropriate storage patterns based on the use case.
Experience designing and developing scalable data pipelines, data integration solutions, and data products.
Proficiency with programming, scripting, and data query languages used to develop and manipulate data solutions.
Experience translating requirements into technical designs and implementing solutions involving multiple data sources.
Knowledge of modern data engineering.
Experience with CDC and orchestration platforms such as AWS DMS, Debezium , Tableflow , Airflow, Databricks Workflows, or equivalent technologies .
Experience using machine learning or AI within data pipelines to classify, enrich, standardize, match, or improve data.
Experience with e-commerce, search, recommendations, or personalization platforms.
Working knowledge of machine learning models and production of ML workflows.
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex (including pregnancy), national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, protected veteran status or any other protected characteristic under federal, state, or local law. We are proud to be an equal opportunity workplace.
We are committed to fostering an inclusive, accessible work environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one’s employment, should you need a reasonable accommodation during the application and selection process, including, but not limited to use of our website, any part of the application, interview or hiring process, please advise us so that we can provide appropriate assistance.