Senior Data Engineer

Grainger is hiring a Senior Data Engineer to design and operate governed batch and real-time data products for Product Discovery, supporting search, machine learning, analytics, and AI-enabled experiences.

Responsibilities

• Design and operate reliable, governed batch and real-time data products using Databricks, Snowflake, Spark, Kubernetes, vector/search technologies, and cloud-native services
• Build pipelines, data assets, orchestration patterns, and search and retrieval capabilities that make trusted data available to search, machine learning, analytics, and engineering teams
• Design, develop, and maintain scalable data solutions to integrate and transform data for business and analytical use
• Apply data engineering practices to deliver reliable, high-quality data products while improving performance, scalability, and automation
• Partner with technical and business stakeholders to translate requirements into effective data solutions
• Design, develop, test, and maintain scalable data pipelines and data products integrating information from multiple sources
• Extract, transform, integrate, and deliver reliable data for analytical and business needs
• Develop and enhance data engineering capabilities to improve data accessibility, performance, quality, and scalability
• Analyze business and technical needs and translate them into data designs, specifications, and solutions
• Identify and implement improvements to data engineering processes, including automation, optimization, and increased reliability
• Resolve data-related challenges with stakeholders and deliver solutions aligned to 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 on architecture, roadmap, adoption, and operational ownership of data capabilities

Requirements

• Bachelor's Degree or equivalent experience in Computer Science, Computer Engineering, Information Systems, Data Science, Software Engineering, or a related technical field
• 3+ years of 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, including selecting patterns based on scale, reliability, and use case
• Experience with containerization and orchestration such as Docker and Kubernetes, plus cloud platforms such as AWS or equivalent
• Experience implementing CI/CD and automated testing using GitHub Actions or equivalent platforms
• Experience working across relational, NoSQL, vector, graph, or other database technologies and choosing 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

Technologies

• Databricks, Snowflake, Spark, Kubernetes
• Vector/search technologies
• Python
• Docker, AWS
• GitHub Actions
• CDC, streaming/event-driven architectures, workflow orchestration
• CI/CD
• NoSQL, graph, relational, vector
• Tableflow, Airflow, Databricks Workflows
• AWS DMS, Debezium
• Machine learning, AI

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

Compensation

• Anticipated base pay range: $104,500.00 - $174,200.00 per year
• Incentive target: eligible for up to 10% (or $), based on individual and company performance objectives per the incentive program terms (subject to change)

Benefits

• Medical, dental, vision, and life insurance plans with coverage starting on day one
• 6 free sessions each year with a licensed therapist for emotional wellbeing support
• 18 paid time off (PTO) days annually for full-time employees (accrual prorated based on employment start date)
• 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

Location and Work Type

• Lake Forest, IL (Hybrid)

Sponsorship

• This position is not eligible for any form of sponsorship now or in the future
• Individuals requiring sponsorship (e.g., OPT or H1B) should not apply
• Only individuals authorized to work in the United States now and for the foreseeable future will be considered