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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** GRAINGER, INC. - **Location:** Chicago, IL, United States (Remote available) - **Experience:** Expert - **Salary:** $112,900.0 - $188,100.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Apache CloudStack, Software Documentation, Databases, Continuous Integration, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Software Debugging, DevOps, Distributed Systems, Python (Programming Language), PostgreSQL, Machine Learning, MongoDB, Cloud Services, Software Engineering, SQL Databases, Google Cloud, Snowflake, Git, Kubernetes, Apache Kafka, Video Streaming, Software Coding, GPT, Software Version Control, Docker, Databricks - **Published:** September 20, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/87856500/1 ## About the Role * Bachelor's degree inData 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, GitHubCopilotand/or ChatGPT * Understanding ofcontainerizationconcepts(Docker, Kubernetes) * Proficient ina cloudstack(AWS, Google Cloud Platform, Azure) and event-streaming technologies (Kafka) * Understanding ofRESTful APIs and how to design performant data models to support them * Excellent communication skills and ability to collaborate effectively with team members. * Understanding ofdistributed system design and experience building production grade distributed systems. * ExperiencewithJava,Pythonand SQLforthe 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, designdocsand incorporate technical requirements for user stories. ## Description 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 H1Bvisastatus) 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 theteam while ensuring alignment with the architectural intents ofthe 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 andmaintaininglogical 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 andJavaScriptbased 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 AItoolingacross data engineering development, CI/CD, and engineering process improvement initiatives. * Optimizeprocessesfor maximum speed, scalability, and reliability. * Partner with stakeholders including data and ML teams, design, product andexecutiveteamsandassistingthem with software and data related technical issues. * Write clean, maintainable, and efficient code following best practices and coding standards. * Troubleshoot, debug, andoptimizeexisting 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 tovalidatethat requirements areclearand 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. ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Speak, Code, Deploy: Transforming Developer Experience with Voice Commands](https://www.wearedevelopers.com/videos/1159-speak-code-deploy-transforming-developer-experience-with-voice-commands) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Best Countries for Software Engineers](https://www.wearedevelopers.com/magazine/267-best-countries-for-software-engineers)