Senior Data Engineer

Grainger is a broad-line distributor serving customers with maintenance, repair, and operating products and value-added solutions through innovative technology and customer expertise. The Senior Data Engineer will lead data architecture design and data engineering initiatives, including data research, ETL, data warehousing, analytics, and business intelligence solutions. The role also involves optimizing systems, supporting CI/CD, mentoring engineers, and collaborating with cross-functional stakeholders.

Responsibilities:

• 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
• Collaborate with engineering teams to effectively apply agentic AI tooling across data engineering development, CI/CD, and engineering process improvement initiatives
• 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 management, and product management to validate that requirements are clear and technical approaches are focused on development of high-quality software
• Work in a collaborative team environment with a focus on continuous improvement and learning, applying teamwork skills such as empathy, engagement, mentoring, knowledge sharing, and constructive feedback

Requirements:

• 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
• Full-time remote candidates are also encouraged to apply. Some travel will be required for team meetings at our corporate offices
• Bachelor's degree in Data Engineering, Software Engineering, related degree, or relevant work experience
• 3+ years of experience with Modern Data Engineering projects and practices: designing, building, and deploying scalable data solutions using AWS, Snowflake, Databricks, Postgres, MongoDB, Kafka
• 3+ years of experience in designing, building, and deploying cloud native solutions
• A working understanding of ML concepts
• Experience with AI code assistant tooling such as, Claude Code, GitHub Copilot and/or ChatGPT
• Understanding of containerization concepts (Docker, Kubernetes)
• Proficient in a cloud stack (AWS, Google Cloud Platform, Azure) and event-streaming technologies (Kafka)
• Understanding of RESTful APIs and how to design performant data models to support them
• Excellent communication skills and ability to collaborate effectively with team members
• Understanding of distributed system design and experience building production grade distributed systems
• Experience with Java, Python and SQL for the variety of software engineering related tasks surrounding data engineering efforts
• Proven experience collaborating across teams to develop and implement software engineering best practices
• Familiarity with version control systems (e.g., Git) and CI/CD pipelines
• Familiarity with Agile/Scrum methodologies and DevOps practices
• Ability to produce detailed, comprehensive software documentation, such as testing plans, requirement specs, design docs and incorporate technical requirements for user stories