Senior Software Engineer, Data Processing

What you will do

• Own a platform, a processing domain, or a multi-team data capability, including both its architecture and its technical roadmap.
• Define the architecture for your domain and write it down clearly enough that teams can build inside it without constant consultation.
• Drive modernization, reliability, scalability, and cost programs that cross team boundaries.
• Solve the systemic problems that show up as recurring incidents, cost escalations, or repeating data-quality defects.
• Influence the technical direction of several teams through design review, written architecture, and working prototypes.
• Set engineering standards for the domain and make them hold without relying on a reporting line.
• Mentor SDE2 and SDE3 engineers and raise the design bar of the whole group, not only of your own projects.
• Stay hands-on through prototypes, critical-path code, and the hardest debugging in the domain.
• Key qualifications
• Bachelor's degree in Computer Science, Software Engineering, a related technical field, or equivalent practical experience.
• 7 to 12 years of professional software engineering experience.
• Ownership of a platform or domain rather than a single system, with architectural decisions that outlived your involvement.
• Deep distributed systems and data-processing expertise at production scale.
• Strong hands-on coding ability that is current, not historical.
• Demonstrated cross-team influence, meaning architecture that other teams adopted because it was right rather than because it was mandated.
• Cloud-native architecture on Azure or equivalent, with real depth on cost, reliability, and security.
• Track record of mentoring senior engineers and improving how a group designs.
• Preferred qualifications
• Healthcare data, clinical informatics, or any other heavily regulated data domains.
• Experience standing up or scaling an engineering site, or a new platform area from zero.
• Governance, lineage, privacy-preserving processing, or large-scale de-identification.
• Public technical writing, conference talks, or sustained open-source contribution.