Work Location Type: HybridReq Number 327958
CompensationThe anticipated base pay compensation range for this position is $112,900.00 to $188,100.00.
Rewards and BenefitsWith 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
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 DetailsGrainger is looking for a Data Engineer for our Data and Analytics team. The Data Engineer will report to a Manager of Data Engineering. The Data and Analytics team's primary mission is to develop analytics by centralizing and integrating high-quality, trusted corporate data in a performant and scalable cloud platform. The Data Engineer will design and develop data pipelines and products in a modern-day, cloud environment. You will work with SMEs, architects, analysts, data scientists and others to build solutions that integrate data from many of our enterprise data sources.
You Will- 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
You Have- 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
