About
Grainger is looking for a Data Engineer for our Data and Analytics team. The Data Engineer will report to a Manager of Data Engineering. The Data and Analytics team's primary mission is to develop analytics by centralizing and integrating high-quality, trusted corporate data in a performant and scalable cloud platform. The Data Engineer will design and develop data pipelines and products in a modern-day, cloud environment. You will work with SMEs, architects, analysts, data scientists and others to build solutions that integrate data from many of our enterprise data sources. This is a Hybrid position requiring 50% of time onsite at either the Chicago, IL or Lake Forest, IL corporate offices. You Will Pioneer a new way of thinking about Data Pipelines, Orchestration and Configuration at Grainger. Design and build scalable data models in Snowflake to support analytics, reporting, and data science use cases. Develop and manage end-to-end data pipelines using Apache Airflow for orchestration, scheduling, and monitoring workflows. Write optimized, maintainable SQL for large-scale data processing, transformation, and validation. 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. You Have Bachelor's Degree or equivalent experience required. 3+ years hands-on experience with Modern Data Engineering projects and practices (Airflow, Kafka, Spark, and python) required. 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 Technology Experience Required: AWS, SQL, Python, Docker/Kubernetes, CI/CD, Git, Snowflake, dbt, Airflow.
Languages
- English
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