Senior Data Engineer

Danfoss is seeking a Senior Data Engineer to join their team in Ljubljana, Slovenia. This role is crucial for enabling energy-efficient heating and cooling solutions, reducing global emissions, and driving cross-divisional data insights for Danfoss Climate Solutions. If you are excited about making a difference, apply now!

Danfoss is a global leader in engineering solutions that increase machine productivity, reduce emissions, and lower energy consumption. With a history dating back to 1933, Danfoss is family-owned, employing over 39,000 people and serving customers in over 100 countries.

Company Overview

Danfoss engineers solutions that increase machine productivity, reduce emissions, lower energy consumption, and enable electrification. Their solutions are used in various sectors including refrigeration, air conditioning, heating, power conversion, and automotive. With a global footprint of 100 factories, Danfoss is committed to innovation and sustainability.

Quick Details

• Salary Range: Not Specified
• Job Type: Full-time
• Experience: 5 Year+
• Qualifications: Not Specified

Key Responsibilities

• Build and optimize scalable data pipelines and data products using modern data engineering tools.
• Develop and maintain data platform infrastructure with a strong focus on scalability and reliability.
• Collaborate with stakeholders across business units and data science teams to define and deliver new features.
• Integrate and harmonize data from multiple departments into a unified ecosystem.
• Contribute to architectural and technical decisions, occasionally supporting hands-on coding.
• Evaluate and adopt emerging technologies to reduce data silos and improve the overall data ecosystem.

Requirements

• Proven experience in software development and data engineering with a strong execution mindset.
• Strong proficiency in SQL and Python; Go, Rust or TypeScript is a plus.
• Experience with orchestration tools such as Airflow, Mage, or Dagster.
• Knowledge of stream processing tools like Kafka, NATS, Flink or similar.
• Experience with Docker, Kubernetes and cloud platforms (Azure, AWS or GCP); Spark and Iceberg are a plus.
• Experience working with time-series databases such as InfluxDB, Victoria Metrics or TimeScaleDB.
• Strong communication skills and ability to collaborate effectively across teams and domains.
• Excellent knowledge of English is required.

Benefits

• Opportunities for promotion from within and support for learning through mentoring, training, and global opportunities.
• Flexibility, autonomy, and support to do your best work while maintaining a healthy work-life balance.
• An inclusive work environment where people of all backgrounds are respected and valued.
• The compensation package includes base salary, performance-based incentive, and benefits.