DelRicht Research
From DelRicht Research's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
We are building a modern, integrated data and AI platform — and this role is a core part of that foundation.
DelRicht Research is a national network of integrated clinical research sites embedded within physicians’ practices that offer the benefit of a dedicated research team with the support of a centralized team.
Our clinical trials provide new treatment options for our patients, and ultimately our goal is to move medicine forward by getting new medications FDA approved. Presently our network stretches across 33 clinical research sites throughout the United States in 18 states.
As DelRicht scales, technology and data are becoming central to how we operate. We are building a modern, integrated data and AI platform — and this role is a core part of that foundation.
This is a high-ownership engineering role for someone who thinks in systems. You will be responsible for designing, building, and maintaining DelRicht's data platform, cloud infrastructure, integration architecture, and AI-powered applications — working across every layer from source systems to operational tools.
Our environment is built on Google Cloud Platform and the broader Google ecosystem. The ideal candidate is deeply comfortable in that stack and brings hands-on experience building AI-augmented workflows using tools such as Vertex AI, Gemini API, Document AI, and LLM-based tooling including Claude and Claude Code.
You will work directly with our existing Data Scientists and business stakeholders to turn operational problems into reliable, scalable, automated solutions.
Data Platform & Architecture
Maintain and evolve DelRicht's centralized BigQuery data warehouse — schemas, datasets, data models, and access controls
Build and maintain ETL/ELT pipelines connecting clinical, operational, financial, and CRM source systems
Design and implement dev, staging, and production environment structure across the data platform
Establish data governance, documentation, and pipeline monitoring standards
Optimize BigQuery performance, query structure, and cost management
Partner with analysts to build trusted, reusable data models rather than one-off datasets
Cloud Infrastructure & DevOps
Design and maintain GCP infrastructure across Cloud Run, Cloud Functions, Cloud Storage, Cloud SQL, Pub/Sub, and IAM
Build and own CI/CD pipelines for data and application deployments
Establish infrastructure-as-code practices and environment parity (dev → staging → production)
Manage service account security, least-privilege access, and GCP IAM governance
Monitor pipelines, set alerting, and maintain platform reliability
AI & Automation
Build and maintain AI-powered pipelines and applications using Vertex AI, Gemini API, Document AI, and related Google AI services
Work fluently with LLM-based development tools including Claude and Claude Code as part of day-to-day engineering workflows
Develop automation that replaces manual, spreadsheet-driven processes with scalable, reliable systems
Evaluate and integrate emerging AI tooling where it creates genuine operational leverage
Integrations & APIs
Build and maintain integrations across operational systems including CRIO, Salesforce, Greenhouse, and financial platforms
Design scalable API integrations using REST, webhooks, and managed platforms such as Fivetran
Own integration reliability, monitoring, and failure handling
Maintain and improve MuleSoft or successor integration middleware where applicable
Google Workspace & Apps Script
Build automation and lightweight applications integrated with Google Sheets, Drive, Gmail, and Workspace APIs
Migrate manual Sheets-based workflows to purpose-built, maintainable solutions
Develop advanced Apps Script solutions as operational bridges while longer-term platform solutions are built
Application Development
Build internal tools and lightweight applications that support operational teams
Write clean Python and/or Node.js backend code for services, APIs, and automation
Develop simple front-end interfaces where needed — comfort with React or equivalent is a plus, but this is not primarily a frontend role
Required
4+ years of professional experience in data engineering, platform engineering, or a closely related technical discipline
Strong, hands-on BigQuery experience — data modeling, SQL optimization, schema design
Fluency in Python for data pipelines, API integrations, and automation
Experience building and maintaining ETL/ELT pipelines in a cloud environment
Hands-on GCP experience across Cloud Run, Cloud Functions, Cloud Storage, and IAM
Experience building and maintaining REST API integrations and webhooks
Strong understanding of environment management (dev/staging/production), CI/CD pipelines, and deployment practices
Experience with service account security and cloud IAM governance
Strong SQL skills and ability to write complex analytical queries
Ability to take technical projects from business requirements through production deployment independently
Strong communication skills — able to work directly with non-technical stakeholders
Strongly Preferred
Hands-on experience with Vertex AI, Gemini API, Document AI, or comparable AI/ML cloud services
Experience working with LLM-based tooling (Claude, Claude Code, OpenAI, or similar) in a production or near-production context
Experience with Fivetran or comparable managed integration platforms
Salesforce integration experience — APIs, data model understanding, or middleware
Looker or Looker Studio dashboard and data model development
Google Apps Script development
Infrastructure-as-code experience (Terraform or Cloud Deployment Manager)
Experience in healthcare, clinical research, or another regulated industry
Nice to Have
Familiarity with HIPAA and clinical data privacy requirements
Experience with data orchestration tools such as Airflow or comparable
Docker and containerization experience
Frontend development experience (React, TypeScript)
Experience with n8n or similar workflow automation platforms
What Success Looks Like
In your first six months, you will have a clear understanding of DelRicht's full data and integration architecture, have contributed meaningfully to pipeline reliability and environment structure, and have shipped at least one automation or integration that materially reduces manual work for an operational team.
Over the first year, you will be a trusted technical owner of DelRicht's data platform — capable of taking projects independently from requirements to production, building AI-augmented workflows that scale with the business, and helping establish the engineering standards that support DelRicht's next stage of growth.
This is a rare opportunity to have genuine ownership across an organization's entire data and technology infrastructure at a moment when that infrastructure is actively being built. You will work on real operational problems, ship tools that teams use every day, and help define the technical architecture that carries the company forward.
We are building a modern, AI-native data platform in a domain — clinical research — where the work directly impacts patient outcomes and the advancement of medicine. If you enjoy building, owning outcomes, and working at the intersection of data, AI, and real operational complexity, this is the right environment.
Scores your resume against this job the way resume scanners do: the job's hard and soft skills, searchability, recruiter tips and formatting.
Create a free account to see your score. Your resume stays in this browser until then, and we never store it.
Already a member? Sign in