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Project Overview :
- Service-oriented architecture but be prepared to deal with legacy code as well as monolithic services based on the Django framework;
- Two main stacks : Python and Java :
- Python services are mostly written using AsyncIO frameworks and libraries, but we also have Django-based services and a lot of Celery workloads;
- Java services based on Spring Boot with custom extensions, Java 11, and Gradle as a build tool;
- AWS and K8S are used extensively for provisioning and deploying workloads;
- The main cross-service communication transports :
- NATS is our main RPC transport, but we’re migrating to gRPC to eliminate the single point of failure with NATS
- Kafka and Debezium for event-based operations
- RabbitMQ is a transport for Celery, but we look forward to migrating to Temporal.io
- Temporal.io as a new promising solution
- LGTM stack and Sentry for monitoring, alerting, and distributed tracing
Requirements :
At least 5+ years of development experience with Python;Care about quality and you know what it means to ship high-quality code;Experience with the Django framework;Experience with microservice-based architectures;Experience with any relational databases (SQL queries, migrations, optimization);Experience with message queues (e.g., RabbitMQ, NATS, Kafka);Put yourself in the shoes of your users and be a steward of crafting great experiences;Strong communicator. Explaining complex technical concepts to product managers, designers, customer support, and other engineers is no problem for you;Experience in software and API design is a must;Communicate effectively in English, both spoken and written;We have tasks in Java from time to time (about 10%), so readiness to write in Java is appreciated.Willingness to engage and contribute with our frontend projects is a plus.Responsibilities :
Collaborate with Engineers, Product Managers, Product Designers and Analysts across PandaDoc to create positive customer impact together.Write clean, self-explainable testable, production-ready code considering all non-functional requirements and limitations (scalability, performance, etc).Follow a feature through its entire lifetime from problem formulation to solution delivery.Use quality metrics to identify gaps and define targets for their team deliverables.Improve our internal processes and documentation.