Data Engineer II
Role details
Job location
Tech stack
Job description
We're hiring a Data Engineer II for the Supply Chain Optimization - Machine Learning Engineering team. The team's mission is to ensure the durability and scalability of machine learning and operations research models that drive impactful results across our supply chain.
This role centers on designing and developing data pipelines and products that support advanced analytics. It involves close collaboration with machine learning engineers and data scientists to set up pipelines for model development and deployment, automate workflows, and maintain the data infrastructure behind key data products.
Expect to work closely with subject matter experts, architects, analysts, and other stakeholders to integrate data from a wide range of enterprise sources. The position reports to the Senior Manager, Machine Learning Engineering.
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.
You Will
- Enable analytics and reporting by centralizing and integrating high quality, large, complex data sets in a performant and scalable cloud platform
- Identify, design, and implement 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 multiple data sources
- Build frameworks, standards & product features to enable self-service analytics
- Partner with stakeholders including data, design, product and executive teams and assisting them with data-related technical issues
Requirements
- Bachelor's Degree or equivalent experience in Engineering or Computer Science or Information Technology, or a related technical discipline required
- 1+ years of experience with Modern Data Engineering projects and practices required
- 1+ years of experience deploying cloud native solutions required
- 1+ years of experience with AWS, SQL, Python, Docker/Kubernetes, CI/CD, Git familiarity with: Snowflake, DBT, Airflow required
- Experience with advanced analytics and machine learning
- Familiarity with BI tools such as Tableau, PowerBI
Benefits & conditions
The anticipated base pay compensation range for this position is $60,400.00 to $100,700.00., With 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.
