Data Scientist

DelRicht Research is building a modern, AI-native data platform for clinical research, with a role that centers on real ownership. You will design, build, and maintain the data platform, cloud infrastructure, integration architecture, and AI-powered applications on Google Cloud Platform. The work connects operational teams with scalable automation, helping replace manual, spreadsheet-driven workflows with dependable systems that support everyday operations.

This onsite position in Metairie, LA focuses on reliable, scalable engineering across the full lifecycle, from environment structure and CI/CD to monitoring, governance, and production deployments.

Responsibilities

• Maintain and evolve DelRicht’s centralized BigQuery warehouse including schemas, datasets, data models, and access controls
• Build and maintain ETL/ELT pipelines connecting clinical, operational, financial, and CRM source systems
• Design dev, staging, and production environment structure across the data platform
• Establish data governance, documentation practices, and pipeline monitoring standards
• Optimize BigQuery performance, query structure, and cost management
• Partner with analysts to deliver trusted, reusable data models instead of one-off datasets
• Design and maintain GCP infrastructure across Cloud Run, Cloud Functions, Cloud Storage, Cloud SQL, Pub/Sub, and IAM
• Own CI/CD pipelines for data and application deployments
• Apply infrastructure-as-code practices and environment parity (dev, staging, production)
• Manage service account security using least-privilege access and GCP IAM governance
• Monitor pipelines, implement alerting, and maintain platform reliability
• Build AI-powered pipelines and applications using Vertex AI, Gemini API, Document AI, and related Google AI services
• Use LLM-based development tools including Claude and Claude Code as part of day-to-day workflows
• Develop automation that replaces manual spreadsheet-driven processes with scalable, reliable systems
• Evaluate and integrate emerging AI tooling where it creates operational leverage
• 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
• Build automation and lightweight apps 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 platform solutions are built
• Build internal tools and lightweight applications that support operational teams
• Write clean backend code in Python and/or Node.js for services, APIs, and automation
• Provide simple front-end interfaces when needed, with comfort in React considered a plus

Requirements

• 4+ years of professional experience in data engineering, platform engineering, or a closely related technical discipline
• Strong, hands-on BigQuery experience including data modeling, SQL optimization, and 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, 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, including working directly with non-technical stakeholders

Preferred Qualifications

• 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 production or near-production contexts
• Experience with Fivetran or comparable managed integration platforms
• Salesforce integration experience including 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
• Familiarity with HIPAA and clinical data privacy requirements (nice to have)
• Experience with data orchestration tools such as Airflow or comparable (nice to have)
• Docker and containerization experience (nice to have)
• Frontend development experience (React, TypeScript) (nice to have)
• Experience with n8n or similar workflow automation platforms (nice to have)

How Success Is Measured

• Within the first six months: develop a clear understanding of DelRicht’s full data and integration architecture; contribute meaningfully to pipeline reliability and environment structure; ship at least one automation or integration that materially reduces manual work for an operational team
• Over the first year: become a trusted technical owner of DelRicht’s data platform; take projects independently from requirements to production; build AI-augmented workflows that scale with the business; help establish engineering standards supporting the company’s next stage of growth

Technologies

• Google Cloud Platform, BigQuery, ETL/ELT, Cloud Run, Cloud Functions, Cloud Storage, Cloud SQL, Pub/Sub, IAM, CI/CD
• Vertex AI, Gemini API, Document AI, LLM-based tooling, Claude, Claude Code
• REST, webhooks, Fivetran, MuleSoft, Google Sheets, Drive, Gmail, Workspace APIs, Apps Script
• Python, Node.js, React

Why DelRicht Research

• Rare chance to have genuine ownership across an organization’s data and technology infrastructure as it is actively being built
• Work on real operational problems and ship tools teams use every day
• Define the technical architecture that carries the company forward
• Build an AI-native data platform in clinical research where the work directly supports patient outcomes and advancement of medicine