Data Engineer

Rad AI

Senior Data Engineer at Rad AI, designing data architecture for scalable healthcare AI solutions. Collaborating with teams to develop and maintain data infrastructures supporting healthcare analytics.

Posted 7/9/2026full-timeSan Francisco • California • 🇺🇸 United StatesMid-LevelSenior💰 $145,000 - $190,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing scalable data architectures and distributed data pipelines using big data technologies. Proficient in ensuring data quality, integrity, and security while collaborating with stakeholders to meet data needs.

Highest-signal resume keywords

Data Engineering ExperienceDistributed Data Pipeline DevelopmentBig Data Processing TechnologiesAWS Services ExpertiseWorkflow Orchestration with Metaflow

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Architecture DesignData Pipeline DevelopmentData Quality AssuranceData Validation ImplementationBig Data AnalyticsSQL Database ManagementNoSQL Database ManagementContainerization with DockerOrchestration with KubernetesSpark Framework

Soft Skills

CollaborationOwnershipProblem-Solving

Tools & Technologies

MetaflowAmazon EMRAWS BatchAWS DynamoDBElasticSearchPostgresql

Industry Keywords

Data EngineeringData InfrastructureData ProcessingData ProductsData Security

Tech Stack

Tools & technologies

AWSDockerDynamoDBElasticSearchKubernetesNoSQLPostgresSparkSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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