Help establish engineering standards and operational practices for a growing ecosystem of internally developed applications and AI-enabled tools.
Support internal builders using Claude Code and related AI development environments by providing guidance around source control, modular design, testing, deployment, documentation, and maintainability.
Help implement production-grade operational practices across internal systems, including monitoring, alerting, incident response, deployment workflows, environment management, uptime management, and post-incident review processes.
Maintain and expand the company’s Azure Fabric Lakehouse architecture across bronze, silver, and gold layers.
Build and monitor ingestion pipelines, improve reliability and observability, resolve data quality issues, and help translate business questions into well-modeled reporting datasets and semantic layers.
Work directly with operational, billing, credentialing, and clinical leadership to support reporting requests, operational tooling, and scalable self-service data access.
Requirements
4+ years building and supporting production software systems, data platforms, or cloud infrastructure
Strong software engineering fundamentals, including Git workflows, testing, modular architecture, debugging, and code review
Strong SQL and Python skills
Experience building and maintaining production ETL/ELT pipelines
Experience working in cloud environments such as Azure, AWS, or GCP
Comfort operating across both application engineering and data engineering domains
Experience supporting or deploying internal operational software systems
Familiarity with modern AI-assisted development workflows and tools such as Claude Code, Copilot, Cursor, or similar environments
Understanding of security and governance principles for regulated or sensitive data environments
Strong communication skills and ability to work directly with non-technical stakeholders
Ability to independently own technical systems end-to-end