About the position
Grainger is looking for a Data Engineer for our Marketing Technology team. The Data Engineer will report to a Senior Manager of Marketing Technology. The Marketing Technology team's primary mission is to integrate, maintain, and optimize a broad range of technology systems & tools used by the Marketing Organization to execute best-in-class marketing programs as well as the data pipelines supporting them. This position will manage the technical development, execution, and maintenance of outbound data pipelines and feeds by centralizing and integrating high-quality, trusted corporate data in a performant and scalable cloud platform and by leveraging the integrated systems and APIs to automate data delivery. The Data Engineer will design and develop data pipelines and products in a modern-day, cloud environment. You will work with SMEs across the Marketing Organization as well as architects, analysts, data scientists and others to build solutions that integrate data from many of our enterprise data sources. Hands-on experience with Data Engineering projects supporting Marketing activation data needs and process automation initiatives is preferred. This is a Hybrid position that requires onsite work (Lake Forest) 3 days per week.
Responsibilities
- Pioneer a new way of thinking about Data Pipelines, Orchestration and Configuration at Grainger.
- Develop our next-generation micro-services to enhance and mature a data-driven culture.
- Help develop the Analytics and Data Kubernetes products in AWS.
- Experience building data products for Data Science use cases.
- Assemble complex sets of data that meet requirements.
- Identify and design 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 data sources.
- Build product features to allow self-service analytics.
- Work with partners including data, design, product and executive teams and assisting them with data-related technical issues.
Requirements
- 3+ years of hands-on experience with Modern Data Engineering projects and practices (Airflow, Kafka, Spark, and python)
- Successful track record in developing and automating large-scale, high-performance data engineering systems (batch and streaming).
- Experience with both scripting and system programming languages (Python and Scala).
- Experience with microservices including defining and testing APIs.
- Experience architecting, developing, and deploying both offline and online feature stores.
- Experience leading data integration efforts of data sources.
- Experience partnering with internal departments (Supply Chain, Marketing, Finance, and HR) to establish requirements.
- Develop junior team members through modern cloud-based development.
- Translate requirements into technical requirements and produce required source-to-target data mappings.
- Bring complex concepts into our organization and mentor others.
- Experience with advanced analytics and machine learning.
Nice-to-haves
- Technology Experience Required: AWS, SQL, Python, Docker/Kubernetes, CI/CD, Git, Snowflake, dbt, Airflow.
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.
