• Serves as a Principal Data Engineer: to design, develop and implement end-to-end data pipelines for ingestion, transformation, and distribution • Collaborates closely with architects, product managers, analytics teams, and platform engineers to align data solutions with business needs • Optimizes data platforms for performance, scalability, cost efficiency, and reliability • Defines and enforces data quality standards, implementing automated validation and monitoring • Provides primary or backup production support for applications and components

Deployed Software Engineer Location San Francisco, CA or Remote (USA) Employment Type Full time Location Type Remote Department Engineering, Product, and Design Engineering Compensation - Base SalaryBase Salary $160K – $215K • Offers Equity Fieldguide’s Total Rewards philosophy is to ensure holistic and competitive compensation that not only attracts and retains top talent but also fosters a culture of accountability and ownership in all the regions where we operate. Our salary ranges are determined by role, level, and location tier to ensure pay aligns with local market conditions and ensures fairness, transparency, and the recognition of employees' contributions. Job compensation ranges may span multiple career levels. The actual base pay for the successful candidate will depend on several factors, including location tier, transferable or job-related skills, work experience, relevant training/certifications, business needs, and market demands. Salary ranges are subject to change and may be adjusted in the future.

• Design, develop, and maintain full-stack internal tools to streamline workflows and improve operational efficiency. • Automate processes and workflows using modern programming languages and frameworks (e.g., Python, JavaScript, Hack). • Build and enhance backend systems to support data management and operational needs. • Establish and advise on technical best practices for software development. • Collaborate with cross-functional partners (e.g., attorneys, Data Science, Data Engineering) to gather requirements and provide technical counsel. • Create and maintain internal documentation for tools, systems, and workflows. • Stay up to date on new technologies and internal systems relevant to operational excellence.

• Architect, build, and maintain the HiveMQ platform software for IoT deployments • Create self-healing software systems • Develop and implement concurrent and performant algorithms • Refactor existing codebases and extend APIs • Improve test coverage and address security vulnerabilities • Identify and eliminate performance bottlenecks