Remote Senior AI-Driven Data Engineer for Clinical Data

Inductive Quotient Analytics; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Inductive Quotient Analytics is seeking a Senior Translational Data and AI Engineer to modernize ingestion, transformation, and delivery of biomarker and clinical data on an AWS-native lakehouse. You will join a hands-on team, expanding end-to-end pipelines across studies and providing reliable data to analytics, AI, and visualization tools.

You will work with scientists and the lead engineer to implement scalable, guarded workflows, production-ready tests, and reproducible pipelines, while

Qualifications

• AI-native engineering practice: building systems around AI coding agents with guardrails, not just prompting.
• 4+ years of professional data engineering on AWS with production pipelines.

Responsibilities

• Build and maintain orchestrated ingestion pipelines for external genomics, proteomics, and other assay data sources.
• Develop and harden layered transformation models (staging, intermediate, mart) with data quality guardrails.
• Implement clinical data ingestion and reconciliation paths against SDTM and ADaM standards.
• Deliver supporting platform infrastructure: APIs, CI/CD, containerized deployments, observability, and data‑warehouse tuning.
• Extract transformation logic from legacy code (R, PySpark) and reconcile with new platform implementations.
• Translate scientific requirements into durable data models and contracts.
• Automate repetitive processes and build guardrails around AI-assisted workflows.
• Participate in design reviews and paired development to improve delivery velocity.

Skills

Python

SQL

AI coding agents

Data engineering

Education

Bachelor's or master’s degree in computer science or related field

Tools

dbt

Dagster

Airflow

Prefect

AWS (S3, ECS/Fargate, Redshift)

Job description

Inductive Quotient Analytics is seeking a Senior Translational Data and AI Engineer to modernize ingestion, transformation, and delivery of biomarker and clinical data on an AWS-native lakehouse. You will join a hands-on team, expanding end-to-end pipelines across studies and providing reliable data to analytics, AI, and visualization tools.

You will work with scientists and the lead engineer to implement scalable, guarded workflows, production-ready tests, and reproducible pipelines, while