Data Engineer

Rad Ai
San Francisco, CA, United States
26 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Big Data Databases Data Architecture Data Validation Information Engineering Data Infrastructure Data Systems Distributed Data Store Amazon DynamoDB Elasticsearch
+9 more
PostgreSQL Machine Learning NoSQL Software Engineering SQL Databases Apache Spark Containerization Amazon Elastic Mapreduce (EMR) Docker

Job 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.

Nice to Haves:

  • Experience working at an early stage startup.
  • Experience in a HIPAA compliant environment.
  • Experience working on machine learning or healthcare related projects.

Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient care-making a meaningful impact on millions of lives. Driven by our mission, we prioritize transparency, inclusion, and close collaboration, bringing together exceptional people to revolutionize healthcare. If you’re passionate about driving innovation and delivering impactful healthcare solutions, we’d love to hear from you!

Benefits & conditions

For US-Based Full-Time Roles, Rad AI offers a variety of benefits, including:

  • 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
  • For roles based outside the US, your recruiter can share more details

At Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

About the company

At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology-saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.

Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others-all backing our mission to empower physicians with cutting-edge AI.

Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.

Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie, and ranked by Deloitte as the 19th fastest-growing company in North America, we are building AI-powered solutions that make a real impact. Most recently, Rad AI was named to CNBC’s Disruptor 50 list, highlighting the innovation and momentum behind our mission.

If you’re ready to shape the future of healthcare, we’d love to have you on our team!

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.dice.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

2:37 min

Comparing traditional SQL tables versus NoSQL non-tabular databases

Stanimira Vlaeva · JS Congress

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · WWC 2025

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

1:59 min

Evolving roles in AI driven software teams

Ignacio Riesgo Ignacio Riesgo +1 · WWC 2024

3:16 min

Terminology differences between relational and NoSQL databases

Tim Faulkes · LIVE

Videos

See all

Related articles

See all