Senior Data Engineer

te a portfolio of high-quality data products in Grainger's purchasing data domain. You will build and improve products in this portfolio by leveraging an end-to-end expertise about the types of insights we seek to generate, the analytics use cases that can drive those insights, the transformations of data in the semantic layer to support the analytics, back to the ingestion of source data that needs to be transformed.

Your responsibilities include constructing data pipelines, performing key data transformations, and educating users about your data products so that analytics and applications can generate insights, drive informed decisions, and continuously innovate.

You will report to the Sr. Manager, Analytics Enablement.

You Will:

• Design, plan, develop, publish, and enhance data products within the purchasing data domain using scalable data processing systems and pipelines on Snowflake, Kubernetes, Databricks, Airflow, Kafka, APIs, and AWS services using Python.

• Identify, plan, prioritize, and execute against a backlog of data acquisition targets that will enhance a purchasing data domain portfolio.

• Build data pipelines and assets that align with the needs of stakeholders of the purchasing data domain, both inside and outside of the supply chain organization.

• Collaborate with technical and non-technical personnel to design, develop, test, and deploy data pipelines and data product increments.

• Modify and enhance previously developed datasets as business conditions and strategies evolve.

• Educate business stakeholders about the data products in your portfolio through live demonstrations and documentation in our enterprise data catalog.

• Informally mentor and assist less experienced data engineers and business analysts.

You Have:

• 5+ years of experience in batch and streaming ETL using SQL, Python, AWS S3, Snowflake, Docker, Airflow, CI/CD, GitHub Actions / Circle CI, DAGs, DBT, GitHub / Bitbucket and data visualization software for Data Engineering or Machine Learning workloads.

• Proficiency in advanced SQL for complex data transformations and query development that optimizes compute performance.

• Working knowledge of how B2B supply chains execute their end-to-end purchasing life cycle from purchase order generation, supplier fulfillment, carrier delivery, warehouse receiving, and payment to supplier.

• Bachelor's degree or equivalent experience in Supply Chain, Computer Science, Data Science, Engineering, or related disciplines.

• Hands-on experience with modern data engineering projects and practices and experience prepping structured and unstructured data for data products.

• Familiarity with containerization and orchestration technologies (Docker, Kubernetes) and experience with shell scripting in Bash, Unix or windows shell is preferable.

• Demonstrated experience implementing data management life cycle, using data quality functions like standardization, transformation, rationalization, linking and matching.

• Experience leading data integration efforts of internal and external data sources.

• Design thinking and product mentality to facilitate common data requirements across multiple stakeholders and use cases.

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.

We are committed to fostering an inclusive, accessible environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one's employment. With this in mind, should you need a reasonable accommodation during the application and selection process, please advise us so that we can provide appropriate assistance.