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# Senior Data Engineer

- **Company:** GRAINGER, INC.
- **Location:** Lake Forest, IL, United States
- **Experience:** Expert
- **Salary:** $104,500.0 - $174,200.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Automation of Tests, Information Systems, Computer Programming, Databases, Computer Engineering, Continuous Delivery, Information Engineering, Data Infrastructure, Data Integration, Data Systems, Distributed Computing Environment, Github, Python (Programming Language), Machine Learning, NoSQL, Software Engineering, Data Streaming, Workflow Management Systems, Scripting, Apache Spark, Event Driven Architecture, Debezium, Kubernetes, Information Technology, Data Management, Machine Learning Operations, Data Pipelines, Docker, Databricks
- **Published:** October 17, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/88632917/1

## About the Role

* 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.

Preferred

 * 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.

## Description

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.

Sponsorship

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.

Youwill

 * Design, develop, test, and maintain scalable data pipelines and data products that integrate information from

multiple sources.

 * 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.