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Senior Data Engineer - Remote

Posted 6 days ago
Data Analysis
Full Time
USA

Overview

At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. We are seeking a Senior Data Engineer to join our engineering team, playing an instrumental role in the construction and maintenance of data collection systems, pipelines, and management tools.

In Short

  • Design and implement data architecture for scalability and efficiency.
  • Define internal standards for maintenance and best practices.
  • Collaborate with researchers to develop data solutions.
  • Take ownership of key data engineering projects.
  • Ensure data quality and security through validation and monitoring.
  • Evaluate and recommend data technologies to improve efficiency.
  • Continuously monitor and improve data infrastructure performance.

Requirements

  • 4+ years of experience in data engineering.
  • Expertise in distributed data pipelines using big data technologies.
  • Hands-on experience with scalable data infrastructure.
  • Experience with AWS services like Amazon EMR.
  • Experience with Spark for large scale data processing.
  • Expertise in workflow orchestration tools like Metaflow.
  • Experience with SQL and NoSQL databases.
  • Hands-on experience with Docker and Kubernetes.
  • Prior Software Engineering experience is a plus.

Benefits

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

Rad AI

Rad AI is a forward-thinking technology company specializing in artificial intelligence solutions for the healthcare industry. The company focuses on enhancing radiology workflows and improving patient outcomes through innovative AI-driven tools. With a commitment to leveraging cutting-edge technology, Rad AI aims to empower healthcare professionals and streamline processes, ultimately transforming the way medical imaging is utilized.

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