Create advanced SQL/Spark SQL queries and prompt-engineered LLM workflows to transform healthcare claims data into clinical insights and automated policy tools. Requires 3-5 years SQL plus 2-3 years healthcare experience.
140k – 170k
Remote3+ YOEData Engineering
About the role
What You’ll Do
SQL & Data Engineering
Create advanced SQL and Spark SQL expressions for complex calculators, data extractions, and data table construction.
Troubleshoot and fix SQL issues within complex queries and transformations.
Own and maintain libraries of clinical calculators and technical reference definitions used across many top 50 payer clients.
Create data visualizations of medical data points such as glucose levels, mean arterial pressure, and other clinical indicators.
Prompt Engineering
Use prompt engineering to create advanced prompts for medical record research and extractions.
Leverage Claude / OpenAI to answer complex medical identification questions.
Troubleshoot and refine prompt logic to improve accuracy and reliability.
Clinical Collaboration & Delivery
Collaborate with medical and clinical staff to create efficiencies in medical case review processes.
Lead initiatives on advancements in clinical policy building and automation.
Drive sprints regarding new client launches as they relate to clinical policies and clinical case reviews.
Collaborate with data science and engineering teams on clinical case needs.
What You Bring
BS or MS in Healthcare / technical degree or equivalent experience.
3-5 years of advanced SQL experience along with 2-3 years of healthcare experience.
Advanced SQL skills, including the ability to understand and work with Spark SQL.
Intermediate to advanced understanding of medical charts and the data included in them, and health insurance claims.
At minimum, an intermediate understanding of prompt engineering.
Comfortable using Claude / OpenAI to create advanced prompts needed to answer complex medical record identification questions.
Basic understanding of how clinical reviews operationally work in the medical claims space.
Ability to work independently once instructions are given.
Ability to troubleshoot and fix SQL or prompt-related errors within complex queries and prompt statements.
Strong interpersonal communication skills to collaborate with clinical / medical staff as needed.
What We Offer
Work from anywhere in the US. Machinify is digital-first.
Full Medical/Dental/Vision for employees & their families.
Flexible and trusting environment where you’ll feel empowered to do your best work.
Unlimited FTO.
Competitive salary, equity, 401(k) including employer match.
Field Engineer building and deploying data pipelines, integrations, and backend systems for government customers at customer sites. Requires active Secret clearance, Python, ETL, cloud technologies, and >50% onsite availability.
140k – 290k
HybridData Engineering
Data Engineer
TabsNew York, NY
Build core data infrastructure as the first Data Engineer, designing scalable warehouse/lakehouse, data pipelines, and models for KPIs and AI systems. Requires 3-5+ years experience with Python, SQL, and modern cloud data stack in startups.
140k – 195k
On-site3+ YOEData Engineering
Software Engineer, Data Foundations
GleanUnited States
Build and scale data ingestion pipelines and connectors for enterprise SaaS apps, transform unstructured data for AI search and agents, ensure reliability and security at petabyte scale. Requires 3+ years backend/data infrastructure experience with distributed systems.
140k – 265k
Hybrid3+ YOEData Engineering
Software Engineer L3 Data Substrate
TwilioUnited States
As a Software Engineer on the Data & Analytics Platform team, you will design, build, and optimize the data platform to support various data-driven initiatives. You will work with cross-functional teams to architect scalable solutions and implement data infrastructure using modern data technologies.
139k – 204k
Remote5+ YOEData Engineering
Data Engineer
Rad AISan Francisco, CA
Senior Data Engineer building scalable data pipelines, infrastructure, and architecture on AWS using Spark, Metaflow, and orchestration tools. Requires 5+ years data engineering experience with big data technologies; ML/healthcare background is a plus.