Senior Python Engineer Lisboa

Senior Python Engineer
Lisboa
Lisboa, Lisboa, Portugal

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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 Async
IO 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
- service communication transports:

NATS is our main RPC transport, but we’re migrating to g
RPC to eliminate the single point of failure with NATS

Kafka and Debezium for
- based operations

Rabbit
MQ 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
- quality code;

Experience with the Django framework;

Experience with
- based architectures;

Experience with any relational databases (SQL queries, migrations, optimization);

Experience with message queues (e. g. , Rabbit
MQ, 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 Panda
Doc to create positive customer impact together.

Write clean,
- explainable testable,
- ready code considering all
- 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.