Backend Engineer — Event-Driven Data & AI Pipelines

Cph Ai Hub; København; Hybrid; DKK 700,000 - 900,000; Full time

Job summary

Cph Ai Hub is seeking a Backend Engineer to design and build event-driven pipelines and backend services that turn audit and activity data into actionable insights. You will work with the Data & AI team to productionize analytical work, deploying on Azure Databricks and Azure, with APIs delivering outputs to SIEM and collaboration tools.

You will design robust pipelines, manage retries, ensure SLA adherence, and contribute to the evolution of schemas and data contracts.

Qualifications

• Strong experience with C#/.NET backend development.
• Proficient in Python for data processing and pipelines.
• Experience with event-driven and asynchronous systems.
• Design ETL/data pipelines for production environments.
• Experience building REST APIs and streaming interfaces.
• Familiar with Azure Databricks and cloud data platforms.
• Ability to design robust, scalable services and CI/CD pipelines.

Responsibilities

• Build event-driven pipelines in C# and Python processing audit data.
• Develop backend services and APIs for product UI, SIEM, and tooling.
• Create enrichment, detection, and scoring components with clear schemas.
• Operate and monitor services across Azure and Databricks, with observability.

Skills

C#/.NET backend

Python for data processing

Event-driven architectures

ETL pipelines

API design (REST, streaming)

Azure Databricks / Azure

Production-grade software

CI/CD practices

Tools

RabbitMQ

Kafka

Azure AKS / Docker

GitHub Actions

Job description

Cph Ai Hub is seeking a Backend Engineer to design and build event-driven pipelines and backend services that turn audit and activity data into actionable insights. You will work with the Data & AI team to productionize analytical work, deploying on Azure Databricks and Azure, with APIs delivering outputs to SIEM and collaboration tools.

You will design robust pipelines, manage retries, ensure SLA adherence, and contribute to the evolution of schemas and data contracts.