Data Scientist

Responsibilities: Maintain and evolve Del Richt’s centralized Big Querywarehouse including schemas, datasets, data models, andaccess controls Build and maintainETL/ELT pipelinesconnecting clinical, operational, financial, and CRM source systems Design dev, staging, and production environment structure across the data platform Establishdata governance, documentation practices, andpipeline monitoringstandards Optimize Big Query performance, query structure, andcost management Partner with analysts to deliver trusted, reusable data models instead of one-off datasets Design and maintainGCP infrastructureacross Cloud Run, Cloud Functions, Cloud Storage, Cloud SQL, Pub/Sub, andIAM OwnCI/CD pipelinesfor data and application deployments Applyinfrastructure-as-codepractices and environment parity (dev, staging, production) Manageservice account securityusing 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 Claudeand Claude Codeas 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 includingCRIO, Salesforce, Greenhouse, and financial platforms Design scalable API integrations usingREST, webhooks, and managed platforms such as Fivetran Own integration reliability, monitoring, and failure handling Maintain and improve Mule Soft (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 Scriptsolutions as operational bridges while platform solutions are built Build internal tools and lightweight applications that support operational teams Write clean backend code in Pythonand/or Node.jsfor services, APIs, and automation Provide simple front-end interfaces when needed, with comfort in Reactconsidered a plus

Requirements: 4+ yearsof professional experience in data engineering, platform engineering, or a closely related technical discipline Strong, hands-on Big Queryexperience including data modeling, SQL optimization, and schema design Fluency in Pythonfor data pipelines, API integrations, and automation Experience building and maintainingETL/ELTpipelines in a cloud environment Hands-onGCPexperience across Cloud Run, Cloud Functions, Cloud Storage, andIAM Experience building and maintainingREST API integrationsand webhooks Strong understanding of environment management (dev/staging/production), CI/CD, and deployment practices Experience with service account security andcloud 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 withLLM-based tooling(Claude, Claude Code, OpenAI, or similar) in production or near-production contexts Experience with Fivetranor 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 Scriptdevelopment Infrastructure-as-codeexperience (Terraform or Cloud Deployment Manager) Experience inhealthcare, clinical research, or another regulated industry Familiarity withHIPAAand clinical data privacy requirements (nice to have) Experience with data orchestration tools such as Airflowor comparable (nice to have) Docker and containerization experience (nice to have) Frontend development experience (React, Type Script) (nice to have) Experience withn 8nor similar workflow automation platforms (nice to have) How Success Is Measured Within the first six months: develop a clear understanding of Del Richt’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 Del Richt’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, Big Query, 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, Mule Soft, Google Sheets, Drive, Gmail, Workspace APIs, Apps Script Python, Node.js, React Why Del Richt Research Rare chance to havegenuine ownershipacross 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