Staff Software Engineer L6

The Staff Software Developer L6 will drive the technical design and execution of our core data platforms and full-stack applications. In this role, you will bridge data engineering (Snowflake, AWS) with full-stack development (Java, Python, UI) while ensuring our applications are highly observable and resilient. As an L6 engineer, you will look beyond individual features to design systems that handle complex data scenarios, lead team technical choices, and safely integrate AI-driven development tools into our daily coding workflows.

[data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAALSURBVBhXY2AAAgAABQABqtXIUQAAAABJRU5ErkJggg==]

Responsibilities

Technical Design & Execution

- System Design: Design and build reliable, scalable distributed data pipelines and full-stack application architectures across AWS and Snowflake.

- Full-Stack Development: Write clean, high-performance code across the entire stack—from Java and Python backends to user-facing UI components.

- Solve Ambiguous Technical Challenges: Take vague or complex product requirements and turn them into concrete, well-documented technical designs that the team can execute.

- Modernize Data Pipelines: Optimize big data processing systems using Spark, EMR, and Glue to process healthcare data efficiently.

AI-Driven Development & Team Mentorship

- Practical AI Adoption: Actively use and promote modern AI development tools (like GitHub Copilot, Claude Code etc) to speed up prototyping, testing, and debugging.

- Code Quality & Validation: Establish guidelines so that the team uses AI tools responsibly, ensuring all AI-generated code is thoroughly reviewed, tested, and secure.

- Technical Mentorship: Mentor senior and mid-level engineers through design reviews and pair programming, helping them level up their engineering practices.

-

Observability & Operations

- Build for Reliability: Implement end-to-end observability frameworks (metrics, logs, and distributed tracing) to ensure deep system visibility and quick incident resolution.

- Automation: Improve CI/CD pipelines and infrastructure-as-code to make deployments seamless and automated.

- Security & Healthcare Standards: Ensure all designs and implementations strictly adhere to healthcare data security requirements and HIPAA compliance.

[data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAALSURBVBhXY2AAAgAABQABqtXIUQAAAABJRU5ErkJggg==]

Qualifications

Core Engineering Experience

- Proven Track Record: 10+ years of professional software engineering experience, with experience leading technical designs and engineering choices for a team.

- Data Ecosystems: Strong experience with modern cloud data warehouse architectures, advanced SQL performance tuning, and distributed data processing frameworks or managed data integration tools.

- Cloud Infrastructure: Hands-on experience building scaleable systems utilizing container orchestration frameworks, serverless computing modules, state machine orchestrators, and cloud object storage solutions.

Polyglot Full-Stack Capabilities

- Backend Mastery: Strong programming expertise in Java and Python for building APIs, microservices, and data scripts.

- UI Exposure: Practical experience with modern UI frameworks (e.g., React or Angular) to effectively connect front-end interfaces with heavy data engines.

- Observability Foundations: Practical experience setting up monitoring and tracing platforms (e.g., Datadog, OpenTelemetry, Prometheus, or ELK) to manage production health.

AI & Leadership Qualities

- AI Innovations: Hands-on experience architecting retrieval-augmented generation (RAG) pipelines, managing vector embeddings, and integrating large language models.

- AI Tooling Comfort: Hands-on experience using generative AI tools inside your daily development workflow