Databricks Data Engineer — Lakehouse & Python Pipelines

Knowit; Göteborgs kommun; Hybride; SEK 700 000 - 1 000 000; Plein temps

Avantages offerts par ce poste

Flexible work setup

Résumé du poste

Knowit in Gothenburg is seeking a Databricks Specialist / Data Engineer to design, build and orchestrate modern cloud-based data platforms with Databricks and Python at the core. You will work within a strong competence network in Cloud, Data, and AI, collaborating with clients to deliver scalable, future-proof data solutions.

You will design data platforms, build pipelines with Python/PySpark, and apply data governance practices such as Unity Catalog while integrating analytics, BI, and ML

Qualifications

• Solid foundation in data engineering with several years in modern data environments.
• Deep interest in Databricks and a drive to deepen expertise on the platform.
• Strong Python and PySpark skills with experience on cloud-based data platforms.
• Experience with data governance and orchestration, e.g., Unity Catalog, is a plus.

Responsabilités

• Designing and developing scalable data platforms based on Databricks and Lakehouse architecture.
• Building, optimizing, and orchestrating data pipelines using Python and PySpark.
• Working with data governance and management through Unity Catalog.
• Integrating data with BI, AI, and ML solutions to create real business value.
• Supporting clients in establishing secure, robust, and future-proof data engineering solutions.

Connaissances

Databricks

Python

PySpark

Azure

AWS

Google Cloud

Data engineering

Unity Catalog

Outils

Databricks

Unity Catalog

Description du poste

Knowit in Gothenburg is seeking a Databricks Specialist / Data Engineer to design, build and orchestrate modern cloud-based data platforms with Databricks and Python at the core. You will work within a strong competence network in Cloud, Data, and AI, collaborating with clients to deliver scalable, future-proof data solutions.

You will design data platforms, build pipelines with Python/PySpark, and apply data governance practices such as Unity Catalog while integrating analytics, BI, and ML