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Senior Software Engineer - Data Engineering

DatabricksAarhus, Denmark
On-site Full-time

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Experience Level

Senior

Qualifications

What We Look For: A Bachelor’s degree or higher in Computer Science or a related field. Over 5 years of hands-on experience in production environments using languages such as Java, Scala, Go, Python, and SQL. A minimum of 2 years of professional experience in Data Engineering or Data Science. Proven experience in developing large-scale distributed systems. Familiarity with cloud technologies, including AWS, Azure, GCP, Docker, or Kubernetes.

About the job

P-1343

Join our team as a Senior Software Engineer with a focus on Data Engineering, where you will be instrumental in driving projects that enhance data analysis and infrastructure within crucial business domains such as cost attribution, capacity forecasting, and efficiency tracking.

Your Impact:

  • Design and develop cost-attribution models: Leverage your data engineering skills combined with a solid understanding of scheduling platforms to create effective systems.
  • Innovate capacity management systems: Ensure operational flexibility, efficiency, and safety across a variety of workloads and environments.
  • Establish systems for operational efficiency: Automatically balance efficiency and safety through the monitoring, forecasting, and proactive management of capacity demands across systems.
  • Create foundational data models and telemetry pipelines: Build metrics that enhance product-wide system reliability and efficiency, providing end-to-end visibility and actionable insights for other teams.

About Databricks

Databricks is a leading data and AI company that empowers over 10,000 organizations globally, including Comcast, Condé Nast, and more than half of the Fortune 500, with its Data Intelligence Platform. Our mission is to unify and democratize data, analytics, and AI. Headquartered in San Francisco, Databricks was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake, and MLflow. Join us in shaping the future of data.

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