Senior Data Engineer

About the role

Grainger is a leading broad line distributor with operations primarily in North America and Japan. This position is eligible for an incentive target of up to 10% of the base pay, based on the achievement of individual and company performance objectives.

Responsibilities

• 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, Postgres, and Databricks user defined function (UDF) definition, authoring and reviewing complex analytical queries, and more.
• Ensure that data architecture and data accessibility strategy create a foundation for future investment in business intelligence and collaboration.
• 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.
• Design and develop the data warehouses.
• Design and implement new business intelligence solutions and ETL processes.
• 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 assist 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

• 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.

Qualifications

• None specified

Skills

• Data Engineering
• Software Engineering
• Modern Data Engineering
• Cloud Native Solutions
• Machine Learning Concepts
• AI Code Assistant Tooling
• Containerization Concepts
• RESTful APIs
• Distributed System Design
• Java
• Python
• SQL
• Agile/Scrum Methodologies
• DevOps Practices
• Version Control Systems
• CI/CD Pipelines
• Software Documentation

Benefits

• 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.

Pay

The anticipated base pay compensation range for this position is $112,900.00 – $188,100.00.

Schedule

This role is eligible for a hybrid schedule, with some travel required for team meetings at our corporate offices.