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Senior Data Engineer

About Rad AI

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 $60M Series C round led by Transformation Capital, bringing our valuation to $525M. 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.

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

Why Join Us: 

We are seeking a Senior Data Engineer to join our engineering team. Given our large client growth and projected movement in the year ahead, we're seeking to expand this team and add a strong resource on board who will play an instrumental role in the construction and maintenance of data collection systems, pipelines and management tools.

What You’ll Be Doing: 

  • 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.

Who We’re Looking For: 

  • 4+ 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!

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

  • Location Flexibility (Remote-first company!)

  • Flexible PTO policy

  • Annual company-wide offsite

  • Periodic team offsites

  • Annual equipment stipend

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.

Please be vigilant regarding job scams. We advise all candidates to apply directly through our official careers page. Our recruiters will use email addresses with the domain @radai.com or no-reply@ashbyhq.com.

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CEO of Rad AI
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Doktor Gurson
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Average salary estimate

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$120000K
$150000K

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What You Should Know About Senior Data Engineer, Rad AI

Join Rad AI as a Senior Data Engineer and play a vital role in reshaping the future of healthcare through innovative artificial intelligence solutions! At Rad AI, we're passionate about developing AI-driven technologies that enhance patient care and support radiologists in their daily work. As part of our dynamic engineering team, you will be responsible for designing and implementing robust data architectures, ensuring they are scalable and efficient. You'll get to work with cutting-edge pipeline authoring tools like Metaflow and large-scale processing technologies such as Spark. Your collaboration with researchers and stakeholders will ensure that everyone's data needs are met, significantly impacting project outcomes. Ownership of key engineering projects will be yours as you develop and maintain high-quality data solutions that guarantee integrity and security. We're looking for someone with at least 4 years of experience in data engineering who is well-versed in distributed data pipelines and big data technologies, especially in AWS environments. If you're excited to work in a supportive and innovative company that prioritizes transparency and inclusion, and if you're passionate about creating solutions that truly make a difference in healthcare, then Rad AI is the place for you!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at Rad AI
What are the main responsibilities of the Senior Data Engineer at Rad AI?

At Rad AI, the Senior Data Engineer is responsible for designing and implementing scalable data architectures, collaborating with researchers to understand data needs, and developing high-quality data solutions. You will also ensure data quality, integrity, and security, while continuously monitoring and improving the performance of data infrastructure.

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What qualifications do I need to apply for the Senior Data Engineer position at Rad AI?

To apply for the Senior Data Engineer role at Rad AI, you should have 4 or more years of experience in data engineering, expertise in distributed data pipelines, and hands-on experience with big data processing technologies like Spark and AWS services. Familiarity with various database technologies and containerization tools like Docker and Kubernetes will also enhance your application.

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How does Rad AI's Senior Data Engineer position differ from other companies?

The Senior Data Engineer position at Rad AI stands out due to our unique focus on healthcare AI solutions that genuinely impact patient care. You'll be working in a dynamic environment, collaborating closely with researchers and stakeholders to develop innovative data solutions tailored to real-world healthcare challenges.

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What tools and technologies will I use as a Senior Data Engineer at Rad AI?

As a Senior Data Engineer at Rad AI, you will utilize tools and technologies such as Metaflow for pipeline authoring, Spark for large-scale data processing, and various AWS services including Amazon EMR. You will also work with a range of database solutions, both SQL and NoSQL, enhancing your data engineering prowess.

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What kind of impact can I expect to have as a Senior Data Engineer at Rad AI?

In the role of Senior Data Engineer at Rad AI, your work will directly contribute to improving patient care by enabling more efficient and accurate radiology reporting through AI solutions. You'll have the opportunity to innovate, streamline data processes, and support healthcare professionals in making informed decisions that affect millions of lives.

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Common Interview Questions for Senior Data Engineer
Can you explain your experience with designing data architectures?

In answering this question, showcase specific projects where you have designed scalable data architectures. Discuss the tools you used, the challenges faced, and how you ensured the architecture met performance needs.

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How do you ensure data quality and integrity in your projects?

When responding, highlight your approach to implementing data validation, monitoring techniques, and access controls. Provide examples of past projects where you successfully maintained data integrity.

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What big data technologies are you most proficient with, and how have you applied them?

Discuss your proficiency in technologies like Spark and AWS services. Provide concrete examples of how you've used these tools in past projects to process large datasets efficiently.

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How do you handle collaboration with researchers to understand their data needs?

Emphasize your communication skills and your proactive approach. Discuss how you would schedule meetings, create surveys, or gather feedback to ensure that you're accurately capturing their requirements.

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Describe a challenging data engineering problem you faced and how you solved it.

Use the STAR method (Situation, Task, Action, Result) to describe a specific situation. Highlight the complexity of the issue and your thought process in arriving at a solution that worked.

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What experience do you have with data pipeline orchestration tools?

Detail your exposure and experience using tools like Metaflow, discussing how you've used them to automate and manage data workflows effectively in previous roles.

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How do you evaluate and recommend data tools for a project?

Discuss your criteria for evaluating new data technologies, such as scalability, cost, and community support. Provide examples of tools you have successfully recommended in the past and their impact.

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What is your experience with containerization technologies, and why are they important in data engineering?

Talk about your hands-on experience with Docker and Kubernetes, highlighting how these technologies help in creating reproducible environments or simplifying deployments.

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How do you stay updated with the latest trends in big data technology?

Mention resources you rely on, such as tech blogs, webinars, industry conferences, or professional networks. Emphasize the importance of continuous learning in the fast-evolving field of data engineering.

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Why do you want to work at Rad AI specifically?

Your answer should reflect an understanding of Rad AI's mission to transform healthcare with AI solutions. Express your eagerness to contribute to meaningful healthcare results and how your values align with the company's goals.

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Our mission is to empower radiologists with AI — saving radiologists time, reducing burnout, and helping to improve the quality of patient care.

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DATE POSTED
March 29, 2025

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