Software Engineer III, Data Product
New
USFull-TimeSenior
Salary$134,000 – $181,000 (target midpoint ~$157,000)
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Job Details
- Experience
- 6+ years of professional software engineering experience, including at least 2+ years building production full-stack systems.
- Required Skills
- PostgreSQLPythonKafkaFastAPIReact
Requirements
- 6+ years of professional software engineering experience, including at least 2+ years building production full-stack systems.
- Strong expertise in Python backend development, ideally with FastAPI or similar asynchronous frameworks.
- Experience working with event-driven architectures (e.g., Kafka or equivalent) in production environments.
- Solid knowledge of PostgreSQL, including schema design, indexing, and query optimization.
- Production experience with React, including integration with backend APIs and state management.
- Strong understanding of system design, API development, and scalable backend architecture.
- Experience shipping production systems with observability, feature flags, and iterative deployment practices.
- Strong testing discipline (unit and integration testing) and focus on system reliability.
- Ability to write clear technical documentation and communicate complex ideas effectively.
- Curiosity about logistics, shipping systems, or data-driven product decision-making.
Responsibilities
- Design, build, and own components of a high-scale rule evaluation engine powering data-driven product decisions.
- Develop backend services in Python (FastAPI or similar) to support low-latency, high-throughput decision workflows.
- Integrate event-driven systems (e.g., Kafka or equivalent) to process and distribute real-time shipping and logistics data.
- Build and maintain React-based interfaces for rule configuration, evaluation visibility, and system observability.
- Design scalable data models supporting auditability, versioning, and reproducibility of decision outputs.
- Collaborate with Data Science, Analytics Engineering, and Product teams to productionize analytical and ML-driven insights.
- Instrument services with metrics, logging, and tracing to ensure production observability and system reliability.
- Participate in on-call rotations and incident response for owned services.
- Contribute to API design, system decomposition, and cross-team technical architecture discussions.
- Support onboarding, code reviews, and knowledge sharing to elevate team engineering practices.
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