Principal Software Engineer - Distributed Systems

Overview Job Title: Principal Software Engineer - Distributed Data Systems Engagement Type: Direct Hire Location: Remote Work Model: 100% Remote Compensation: $150,000-$214,000 base salary plus 10% bonus Role Overview We are seeking a Principal Engineer - Distributed Data Systems to act as the data authority within our software engineering organization as we move toward autonomous, stream‑aligned teams. This is not a Data Analytics, BI, ETL, or DevOps role. This is a principal‑level backend and software engineering position focused on how production applications design, use, and scale their data systems.

You are not a centralized gatekeeper; you are an embedded technical leader who enables teams to make strong, independent data decisions. You will partner directly with application engineers to improve data modeling, performance, reliability, and scalability in real, customer‑facing systems. Key Responsibilities Serve as the principal expert guiding application‑level data decisions across engineering teams Partner with backend and full‑stack engineers to design scalable, resilient, and cost‑effective data architectures Review application designs and production code to identify data modeling, performance, and scaling risks early Influence standards and best practices for distributed data systems without becoming a bottleneck Optimize live production systems under real traffic through query tuning, indexing strategies, execution plan analysis, and resource optimization Design schemas and data models that support domain ownership, evolution over time, and operational correctness Guide teams on cloud‑native data usage, balancing scalability, reliability, and cost Mentor engineers and elevate organizational understanding of modern data system patterns Required Qualifications Application and Backend Engineering Proven experience building and operating production backend systems Strong understanding of service‑oriented architecture, API design, and runtime considerations Comfortable reviewing backend code and identifying data‑related concerns early in the development lifecycle Distributed Data Systems Expertise Deep, hands‑on experience with relational and NoSQL databases Experience with PostgreSQL, SQL Server, MongoDB, DynamoDB, and/or DocumentDB Strong judgment on trade‑offs between different data models and database technologies Performance, Scale, and Reliability Demonstrated experience optimizing high‑traffic production systems Expertise in query performance tuning, index and schema optimization, execution plan analysis, and cost‑aware scaling Data Modeling and Architecture Experience designing schemas that support domain ownership, system evolution, and correctness Familiarity with event‑driven architectures, data replication and syndication, and temporal data models Deep experience with data platforms in AWS, Azure, or GCP Strong understanding of managed database services, cloud‑native scaling patterns, and cost versus performance trade‑offs Leadership and Communication Proven ability to mentor and educate engineers Ability to influence architectural decisions without formal authority Clear communication skills with engineers and technical leadership All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status.

We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the California Fair Chance Act, City of Los Angeles\' Fair Chance Initiative for Hiring Ordinance, and Los Angeles County Fair Chance Ordinance. #J-18808-Ljbffr