Python Integration Engineer

About the role

Our platform sits between customer‑facing systems and a network of partner and vendor APIs, handling order management, provisioning, contract management and field operations. As a Senior Python Integration Engineer you will design, build and operate REST APIs, webhooks and asynchronous integration services that ensure reliable communication between internal systems and external partners.

Key responsibilities

• Design, develop and maintain Python integration services and REST APIs using Django/DRF, FastAPI or Flask.
• Build webhook consumers and event‑driven pipelines with signature verification, idempotent processing, retries, dead‑letter handling and sequencing.
• Implement asynchronous processing using queues and workers such as AWS SQS, Lambda, Celery or Kafka consumers.
• Configure and manage API gateway solutions (e.g., Kong) including authentication, routing, rate limiting and declarative configuration.
• Ensure data integrity across integrations through schema evolution, data normalisation, reconciliation and version compatibility.
• Monitor, troubleshoot and support production services using dashboards, logging, alerts, tracing and runbooks.
• Manage infrastructure as code with Pulumi or Terraform for development and production environments.
• Improve reliability via code reviews, automated testing, performance optimisation and failure isolation.
• Collaborate with internal engineering teams and external partners to deliver secure, scalable integration solutions.

Required profile

• Minimum four years of professional experience developing backend services in Python with Django/DRF, FastAPI or Flask.
• Strong experience integrating third‑party APIs (OAuth2, JWT, API keys, HMAC, pagination, rate limiting, versioning).
• Proven ability to design and implement asynchronous, event‑driven architectures using SQS, Celery, Kafka or similar.
• Solid knowledge of PostgreSQL including schema design, migrations, transactions and query optimisation.
• Experience deploying cloud‑native applications on AWS using containers and/or serverless technologies.
• Familiarity with structured logging, monitoring, metrics, alerting and production incident management.
• Experience with automated testing (pytest) and CI/CD pipelines.

Required skills

• Python
• Django / DRF
• FastAPI
• Flask
• REST APIs
• Webhooks
• AWS (SQS, Lambda, containers)
• Celery
• Kafka
• Kong (API gateway)
• PostgreSQL
• Pulumi or Terraform
• Structured logging and monitoring (Datadog)
• CI/CD pipelines
• Pytest