Senior Staff Data Engineer

 

Work Location Type: Hybrid 

 

As a leading industrial distributor with operations primarily in North America, Japan and the United Kingdom, We Keep The World Working® by serving more than 4.5 million customers worldwide with products delivered through innovative technology and deep customer relationships. With 2023 sales of $16.5 billion, we’re dedicated to providing value for customers, fostering an engaging culture for team members and driving strong financial results.

 

Our welcoming workplace enables you to learn, grow and make a difference by keeping businesses running and their people safe. As a 2024 Glassdoor Best Place to Work and a Great Place to Work-Certified™ company, we’re looking for passionate people to join our team as we continue leading the industry over our next 100 years.

 

 

Position Details: 

A rapidly growing team at Grainger is focusing on transforming a variety of transactional and operational data, to support the development of new analytical tools and services aimed at providing all of our users, both Customers and Sellers, with reporting, analytics, and actionable insights that save them time and money; resulting in deeper customer relationships and increased market share. #StartWithTheCustomer 

An individual in this role can expect to lead the collaborative design of our data architecture as well as the implementation of a variety of data engineering initiatives including data research and analysis, ETL using Airflow (Astronomer), Snowflake and Databricks user defined function (UDF) definition, authoring and reviewing complex analytical queries, and more.   

This role reports to the Product Engineering Manager and can be based in Lake Forest or Chicago, IL on a hybrid basis. Full-time remote candidates are also encouraged to apply. Some travel will be required for team meetings at our corporate offices. 

 

You Will: 

• Recommend and implement the data architecture and data accessibility strategy for the team while ensuring alignment with the architectural intents of the organization.

• Ensure that data architecture and data accessibility strategy create a foundation for future investment in business intelligence and collaboration.

• Collaborate with business partners, analysts, and solution delivery team members to understand the implications of respective architectures on data architecture and maximize the value of data across the organization. 

• Maintain a holistic view of data assets by creating and maintaining logical data models and physical data base designs that illustrate how data is stored, processed, and accessed in the analytics ecosystem.

• Responsible for the design and development of the data warehouses 

• Responsible for the design and implementation of new business intelligence solutions and ETL processes 

• Design, implement, review  

  • Python based ETL scripts 

  • SQL and JavaScript based UDF 

• Understand trends and emerging technologies and evaluate the performance and applicability of potential tools for our requirements.   

• Optimize processes for maximum speed, scalability, and reliability.  

• Partner with stakeholders including data and ML teams, design, product and executive teams and assisting them with software and data related technical issues.  

• Write clean, maintainable, and efficient code following best practices and coding standards.  

• Troubleshoot, debug, and optimize existing systems to improve performance.  

• Work on and enhance the CI/CD pipelines. 

• Promote effective team practices, shape team culture, and engage in active mentoring.  

• Mentor junior engineers. 

• Collaborate with tech leads, architecture, engineering ma