Staff Data Engineer

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Engineer based in United States.** This role offers the opportunity to lead the architecture and evolution of large-scale data infrastructure within a healthcare technology environment. You will design reliable, scalable data ingestion and transformation systems that support critical clinical and business decisions. Working across engineering, clinical, and operational teams, you will build solutions that improve how complex healthcare data is processed and utilized. The position combines deep technical expertise with leadership, mentorship, and innovation in AI-assisted software development. You will shape engineering standards, introduce automation, and help transform how teams build and maintain data platforms. This is a high-impact opportunity for an experienced data engineer passionate about scalable systems, modern cloud technologies, and meaningful healthcare outcomes. ### Accountabilities: The Staff Data Engineer will serve as a technical leader responsible for designing, building, and optimizing scalable data platforms. This role requires strong architectural judgment, hands-on engineering expertise, and the ability to guide teams toward modern, efficient, and AI-enabled development practices. - Act as a technical architect by leading system design reviews, recommending scalable solutions, and establishing engineering best practices for data infrastructure. - Design and implement scalable data ingestion pipelines capable of processing large healthcare datasets and supporting complex business requirements. - Build reusable, configurable, and containerized pipeline components that enable teams to efficiently manage evolving data needs. - Develop and maintain ETL/ELT workflows using Python, SQL, and dbt, including incremental models, macros, testing strategies, and transformation frameworks. - Create monitoring, alerting, and reliability systems to ensure strong data quality, pipeline health, and operational excellence. - Apply software engineering best practices such as test-driven development, modular architecture, and maintainable system design. - Refactor existing data processes to improve scalability, performance, reliability, and developer efficiency. - Lead the adoption of AI-assisted development practices by establishing workflows for using AI coding tools to accelerate engineering delivery. - Demonstrate effective use of AI agents by reviewing, validating, testing, and taking ownership of AI-generated solutions. - Identify opportunities to automate engineering workflows through AI tooling, including pipeline creation, documentation, data quality improvements, and repetitive development tasks. - Mentor engineers, promote technical excellence, and support knowledge sharing across teams. - Collaborate with technical and non-technical stakeholders to translate complex data challenges into effective solutions. ## **Requirements:** The ideal candidate is a highly experienced data engineering professional with a strong background in large-scale data systems, cloud architecture, and modern software development practices. You should be comfortable leading technical initiatives, working with complex datasets, and driving innovation through automation and AI-enabled engineering. - 10+ years of experience in data engineering, with significant experience designing large-scale data ingestion and infrastructure solutions. - Proven experience building production-grade ETL pipelines using Python, SQL, and dbt. - Strong understanding of ETL/ELT frameworks, distributed data processing, and scalable data architectures. - Hands-on experience using AI coding tools such as Claude Code, Cursor, Copilot, or similar platforms to generate, review, and improve production-quality code. - Strong understanding of AI-assisted development workflows and the ability to validate, test, and take ownership o…