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Data Engineer

Karbone
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About:

Karbone is an award-winning liquidity services provider for energy transition and environmental commodity markets. Since 2008, we've helped clients across global energy markets with revenue hedging, risk management, and market advisory. Our teams are ranked first among their peers and are driven by a shared mission: giving clients the market access, liquidity, and insight they need to succeed in the new energy economy.
 

The Role:

We're looking for a Data Engineer to help us build our cloud data infrastructure on Google Cloud Platform (GCP)  from the ground up. This is a rare opportunity to join at the foundation stage: you'll work on real pipelines, contribute to architecture decisions, and grow alongside the platform you help create. You'll be mentored as you go and given room to take ownership quickly.
 

Responsibilities:

  • Build and optimize cloud-native data pipelines within a clean, scalable GCP environment.
  • Manage PostgreSQL and TimescaleDB systems to support complex geospatial and high-velocity time-series datasets.
  • Develop Python-based ETL/ELT workflows using GCP-native tools like Dataplex, Cloud Run, or Dataflow.
  • Implement monitoring, alerting, and dashboards to maintain data infrastructure health and uptime.
  • Drive the transition to "Infrastructure as Code" using Terraform for reproducible and version-controlled environments.
  • Set up automated CI/CD pipelines via Jenkins or GitHub Actions to replace manual deployment processes.
  • Architect the foundation for Retrieval-Augmented Generation (RAG) using BigQuery’s vector search and Vertex AI.
     

Requirements:

  • A bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related technical field. 
  •  1–2+ years of data engineering experience (internship experience welcome)
  • Solid Python and SQL fundamentals. 
  • Exposure to cloud platforms (GCP or AWS). 
  • Basic understanding of ETL or data pipeline concepts. 
  • Bonus: any experience with Terraform, Docker, GitHub Actions, or database performance tuning