Data Engineer III
About The Position
Grainger is seeking a Data Engineer III to join our Machine Learning Engineering (MLE) team supporting Supply Chain and Inventory Analytics. This role reports to a Senior Manager of Machine Learning Engineering and partners closely with Inventory Reporting & Analysis (R&A). The objective of this role is to deliver high-quality, trusted, and scalable data pipelines that power advanced analytics, optimization, and machine learning. This role will own the data foundation behind ML and analytics use cases, enabling faster decision-making, improving data reliability, and unlocking scalable insights across the business. This position is Hybrid requiring 2 days per week onsite at the Chicago or Lake Forest, IL offices.
Requirements
- Bachelor's Degree or equivalent experience required
- 3+ years hands-on experience with Modern Data Engineering projects and practices (Airflow, Kafka, Spark, and python) required
- Successful track record in developing and automating large-scale, high-performance data engineering systems (batch and streaming).
- Experience with both scripting and system programming languages (Python and Scala).
- Experience with microservices including defining and testing APIs
- Experience architecting, developing, and deploying both offline and online feature stores
- Experience leading data integration efforts of data sources
- Experience partnering with internal departments (Supply Chain, Marketing, Finance, and HR) to establish requirements.
- Develop junior team members through modern cloud-based development
- Translate requirements into technical requirements and produce required source-to-target data mappings.
- Bring complex concepts into our organization and mentor others.
- Experience with advanced analytics and machine learning
- Technology Experience Required: AWS, SQL, Python, Docker/Kubernetes, CI/CD, Git, Snowflake, dbt, Airflow
Responsibilities
- Pioneer a new way of thinking about Data Pipelines, Orchestration and Configuration at Grainger.
- Develop our next-generation micro-services to enhance and mature a data-driven culture
- Help develop the Analytics and Data Kubernetes products in AWS
- Experience building data products for Data Science use cases
- Assemble complex sets of data that meet requirements
- Identify and design internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
- Build required tools for extraction, transformation and loading of data from data sources
- Build product features to allow self-service analytics
- Work with partners including data, design, product and executive teams and assisting them with data-related technical issues
Benefits
- Medical, dental, vision, and life insurance plans with coverage starting on day one of employment
- 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)
- 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.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Associate degree
