[Hiring] Data Engineer @Vattenfall

Role Description

As our new Data Engineer, you will join a collaborative and skilled organization working with data at scale to enable automation of real business cases through data-driven and Machine Learning-based intelligence.

We are hiring two Data Engineers for two closely collaborating teams with different focus areas:

• The Data Science team, working directly with forecasting, analytics, and ML-based decision support.
• The Data Streaming Platform (DSP) team, a newly formed team building and operating a central platform for real-time and event-driven data across the organization.

We work in a Scrum setup and have in recent years been very successful in forecasting both electricity prices and electricity consumption, while at the same time scaling our real-time data capabilities. Your work will have direct and measurable impact.

What will you do?

• Design, build, and operate batch and real-time data pipelines using Azure, Databricks, and Python.
• Ingest and process external and internal data such as weather data, market prices, grid telemetry, and event streams.
• Work with streaming technologies including Kafka, Spark Structured Streaming, and Flink.
• Ensure high data quality through validation, monitoring, and lineage.
• Develop and improve data workflows, standards, and reliability in production systems.
• Dependent on your area of expertise and interest, you will work in either the Data Science- or Data Streaming Platform team.

Data Science team focus:

• Enable forecasting, analytics, and ML use cases with high-quality, well-modelled data.
• Collaborate closely with Data Scientists, ML Engineers, and other engineering teams.

DSP team focus:

• Build Kafka based central streaming data platform from scratch to enable traders, analysts and asset managers to publish and consume live and historical data at scale.
• Operate and continuously enhance the components once the platform is in production.

Location: Katowice or remotely in Poland

Qualifications

• Strong Python and SQL skills.
• Practical experience with cloud data platforms (Azure, Databricks) and with different data storage solutions, including data lakes, lake houses and analytical databases.
• Hands-on experience with streaming systems (Kafka, Spark or Flink).
• Familiarity with Airflow, CI/CD, DevOps practices.
• Experience with Docker, Kubernetes, and Infrastructure-as-Code.
• Understanding of data contracts, time-series data, and event-driven systems.
• Fluency in English and interest in the energy domain.

Benefits

• Good remuneration.
• A challenging and international work environment.
• The possibility to work with some of the best in the field.
• Working in interdisciplinary teams with support from committed colleagues.
• Attractive employment conditions and opportunities for personal and professional development.