Data Engineer

🔥 18 hours ago

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Rad AI

51 - 200 employees

Founded 2018

🔧 Hardware

💰 $25M Series A on 2021-11

Manufacturing • Hardware • Engineering

Rad AI is a company that specializes in custom manufacturing and processing solutions, particularly in the fabrication of components such as casters and material handling devices. They offer a range of products including adjustable casters and OEM parts designed for various industrial applications. Based in Somerset, Michigan, Rad AI is committed to high-quality engineering and manufacturing services.

📋 Description

• Design and implement the data architecture, ensuring scalability, flexibility, and efficiency using pipeline authoring tools like Metaflow and large-scale data processing technologies like Spark. • Define and extend our internal standards for style, maintenance, and best practices for a high-scale data platform. • Collaborate with researchers and other stakeholders to understand their data needs including model training and production monitoring systems and develop solutions that meet those requirements. • Take ownership of key data engineering projects and work independently to design, develop, and maintain high-quality data solutions. • Ensure data quality, integrity, and security by implementing robust data validation, monitoring, and access controls. • Evaluate and recommend data technologies and tools to improve the efficiency and effectiveness of the data engineering process. • Continuously monitor, maintain, and improve the performance and stability of the data infrastructure.

🎯 Requirements

• 5+ years relevant experience in data engineering. • Expertise in designing and developing distributed data pipelines using big data technologies on large scale data sets. • Deep and hands-on experience designing, planning, productionizing, maintaining and documenting reliable and scalable data infrastructure and data products in complex environments. • Solid experience with big data processing and analytics on AWS, using services such as Amazon EMR and AWS Batch. • Experience in large scale data processing technologies such as Spark. • Expertise in orchestrating workflows using tools like Metaflow. • Experience with various database technologies including SQL, NoSQL databases (e.g., AWS DynamoDB, ElasticSearch, Postgresql). • Hands-on experience with containerization technologies, such as Docker and Kubernetes. • Prior Software Engineering experience is a big plus.

🏖️ Benefits

• Comprehensive Medical, Dental, Vision & Life insurance • HSA (with employer match), FSA, & DCFSA • 401(k) • 11 Paid Company Holidays • Flexible PTO policy • Annual company-wide offsite • Periodic team offsites • Annual equipment stipend

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