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Camunda

Open-architecture platform for process automation

Full Stack Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-time$143.8k - $231.9k /yr

About the Job

Requirements

  • The candidate should have experience as a data engineer with machine learning or artificial intelligence experience and be comfortable working in an AI-native environment.
  • The candidate should be willing or able to use Camunda’s product.
  • The candidate should have at least five years of data engineering or machine learning experience.
  • The candidate should have strong data modeling skills and several years of experience with dbt.
  • The candidate should have experience deploying, operating, and evolving cloud data pipelines, including batching and streaming.
  • The candidate should know infrastructure-as-code tools such as Terraform.
  • The candidate should be able to write automated tests to maintain codebase quality.

Responsibilities

  • Build evaluations for the agents that use the Holistic Data Platform, review their answers, identify incorrect answers, and fix the underlying cause in the data, documentation, or prompt context.
  • Build and maintain data ingestion, orchestration, dbt, CI/CD, and cost-control capabilities for the data platform.
  • Help identify where customers are getting stuck and how to better support them using machine learning.
  • Work with the product team to interpret product telemetry and improve the product.
  • Define correctness for important metrics, test and monitor data quality, alert stakeholders when issues occur, and reconcile the Holistic Data Platform against data sources.
  • Enable analysts and business owners to answer questions independently.

About the Company

Camunda

Open-architecture platform for process automation

Camunda provides a digital process automation platform that lets organizations design, execute, and monitor complex business processes across systems. The platform orchestrates end-to-end tasks, automating workflows and enabling AI-driven decisions, with hyperautomation to handle tasks previously done by humans. It uses open architecture to connect with many apps, data sources, and frameworks, enabling broad integration and customization to fit different tech stacks. Its goal is to help businesses improve efficiency, cut costs, and scale automation across departments through a flexible platform and related training and support services.

Company size
501-1,000
Company stage
Series B
Total funding
$117.7M
Headquarters
Berlin, Germany
Founded
2008

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