Senior Data Engineer

Senior Data Engineer

Date: Sep 19, 2026

Location: CHICAGO, IL, US, 60661-4555

Company: Grainger Businesses

Work Location Type: Hybrid

Req Number 333076

About Grainger

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 than 4.6 million customers worldwide with maintenance, repair and operating (MRO) products and value-added solutions delivered through innovative technology and deep customer expertise. Known for its commitment to service and purpose-driven culture, the Company reported 2025 revenue of $17.9 billion. For more information, visit www.grainger.com.

Compensation

The anticipated base pay compensation range for this position is $112,900.00 – $188,100.00. 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.

Rewards and Benefits

With benefits starting on day one, our programs provide choice and flexibility to meet team members' individual needs, including:

Medical, dental, vision, and life insurance plans with coverage starting on day one of employment and 6 free sessions each year with a licensed therapist to support your emotional wellbeing.

18 paid time off (PTO) days annually for full-time employees (accrual prorated based on employment start date) and 6 company holidays per year.

6% company contribution to a 401(k) Retirement Savings Plan each pay period, no employee contribution required.

Employee discounts, tuition reimbursement, student loan refinancing and free access to financial counseling, education, and tools.

Maternity support programs, nursing benefits, and up to 14 weeks paid leave for birth parents and up to 4 weeks paid leave for non-birth parents.

For additional information and details regarding Grainger’s benefits, please click on the link below:

https://experience100.ehr.com/grainger/Home/Tools-Resources/Key-Resources/New-Hire

Grainger Benefits

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.

Position Details

A rapidly growing team at Grainger is focusing on transforming a variety of transactional and operational data, to support the development of new analytical tools and services aimed at providing all of our users, Sellers and Seller Operational Support, with reporting, analytics, and actionable insights that save them time and money; resulting in deeper customer relationships and increased market share. #StartWithTheCustomer

You will lead the collaborative design of our data architecture as well as the implementation of a variety of data engineering initiatives including data research and analysis, ETL using Airflow (Astronomer), Snowflake, Postgres, and Databricks user defined function (UDF) definition, authoring and reviewing complex analytical queries, and more.

You will report to the Product Engineering Manager and can be based in Lake Forest or Chicago, IL on a hybrid basis. Full-time remote candidates are also encouraged to apply. Some travel will be required for team meetings at our corporate offices.

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.

You will

Recommend and implement the data architecture and data accessibility strategy for the team while ensuring alignment with the architectural intents of the organization

Ensure that data architecture and data accessibility strategy create a foundation for future investment in business intelligence and collaboration

Collaborate with business partners, analysts, and solution delivery team members to understand the implications of respective architectures on data architecture and maximize the value of data across the organization

Maintain a holistic view of data assets by creating and maintaining logical data models and physical data base designs that illustrate how data is stored, processed, and accessed in the analytics ecosystem

Responsible for the design and development of the data warehouses

Responsible for the design and implementation of new business intelligence solutions and ETL processes

Design, implement, review

Python based ETL scripts

SQL and JavaScript based UDF

Understand trends and emerging technologies and evaluate the performance and applicability of potential tools for our requirements.

Collaborate with engineering teams to effectively apply agentic AI tooling across data engineering development, CI/CD, and engineering process improvement initiatives.

Optimize processes for maximum speed, scalability, and reliability.

Partner with stakeholders including data and ML teams, design, product and executive teams and assisting them with software and data related technical issues.

Write clean, maintainable, and efficient code following best practices and coding standards.

Troubleshoot, debug, and optimize existing systems to improve performance.

Work on and enhance the CI/CD pipelines.

Promote effective team practices, shape team culture, and engage in active mentoring.

Mentor junior engineers.

Collaborate with tech leads, architecture, engineering management, and product management to validate that requirements are clear and technical approaches are focused on development of high-quality software.

Work in a collaborative team environment with a focus on continuous improvement and learning, applying teamwork skills such as empathy, engagement, mentoring, knowledge sharing, and constructive feedback.

You have

Bachelor’s degree in Data Engineering, Software Engineering, related degree, or relevant work experience.

3+ years of experience with Modern Data Engineering projects and practices: designing, building, and deploying scalable data solutions using AWS, Snowflake, Databricks, Postgres, MongoDB, Kafka

3+ years of experience in designing, building, and deploying cloud native solutions.

A working understanding of ML concepts

Experience with AI code assistant tooling such as, Claude Code, GitHub Copilot and/or ChatGPT

Understanding of containerization concepts (Docker, Kubernetes)

Proficient in a cloud stack (AWS, Google Cloud Platform, Azure) and event-streaming technologies (Kafka)

Understanding of RESTful APIs and how to design performant data models to support them

Excellent communication skills and ability to collaborate effectively with team members.

Understanding of distributed system design and experience building production grade distributed systems.

Experience with Java, Python and SQL for the variety of software engineering related tasks surrounding data engineering efforts

Proven experience collaborating across teams to develop and implement software engineering best practices.

Familiarity with version control systems (e.g., Git) and CI/CD pipelines.

Familiarity with Agile/Scrum methodologies and DevOps practices.

Ability to produce detailed, comprehensive software documentation, such as testing plans, requirement specs, design docs and incorporate technical requirements for user stories.

• Bachelor’s degree or relevant experience with 3+ years in modern data engineering using AWS, Snowflake, Databricks, Postgres, MongoDB, Kafka
• Proficient in cloud-native solution design, Python, Java, SQL, containerization (Docker, Kubernetes), and distributed system design
• Experience with AI code assistant tools, RESTful APIs, CI/CD pipelines, Agile/Scrum, and strong communication skills