Sr. Software Engineer - Data Engineering

Posted 2 Days Ago
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Aarhus, Midtjylland
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
As a Sr. Software Engineer focused on data engineering, you will design cost-attribution models, develop systems for capacity management, and build foundational data models and telemetry pipelines to enhance operational efficiency and safety.
Summary Generated by Built In

P-1343

As a software engineer with a data engineering focus, you will work with your team to drive projects that are centered around data analysis and infrastructure for critical business domains for cost attribution, capacity forecasting and efficiency tracking.  

The impact you'll have:

  • Design and implement cost-attribution models and systems by combining your data engineering expertise with a deep technical understanding of the underlying scheduling platforms.
  • Develop systems that generalize capacity management to ensure flexibility, efficiency, and safety across diverse workloads and environments.
  • Build systems to automatically maintain the right balance between operational efficiency and safety by monitoring, forecasting, and proactively managing capacity demand across systems.
  • Build foundational data models, metrics, and telemetry pipelines to track product-wide system reliability and efficiency—providing end-to-end visibility and empowering other teams with actionable insights.

What we look for:

  • BS (or higher) in Computer Science, or a related field.
  • 5+ years of production level experience in one of: Java, Scala, Go, Python - and SQL.
  • 2+ years of professional experience with Data Engineering or Data Science.
  • Experience developing large-scale distributed systems.
  • Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. 

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Top Skills

AWS
Azure
Docker
GCP
Go
Java
Kubernetes
Python
Scala
SQL
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The Company
New York, NY
2,200 Employees
Year Founded: 2013

What We Do

As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

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