Data Engineer Large Scale Data Platforms 16597
Description
Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry. Assignment Overview We are looking for several experienced Data Engineers What you will work on Developing strategies and architecture for large-scale data collection, processing, and utilization Deg and implementing scalable data pipelines for dense data such as raw sensor signals and service messages Contributing to the development of a Data Mesh platform supporting multiple engineering teams Building and maintaining data infrastructure used for advanced autonomous system development Collaborating closely with teams working in Machine Learning, MLOps, Perception, and Systems Engineering Ensuring efficient ingestion, storage, and processing of large-scale datasets Supporting the continuous improvement of data platforms and engineering workflows What you bring Minimum 5 years of experience in Data Engineering or Software Engineering Educational background in Computer Science, Software Engineering, Mechatronics, or Electronics Experience building and operating large-scale data collection, ingestion, and processing platforms Strong communication skills and ability to collaborate with cross-functional technical teams Ability to work independently in fast-paced development environments Experience with Go or C++ is considered a strong advantage Experience working with Google Cloud Platform (GCP) Experience with multiple database technologies such as PostgreSQL, BigQuery, or Firestore Experience processing large volumes of sensor data such as camera, LiDAR, or radar Understanding of machine learning training workflows and data pipelines
Skills
Want AI to find more roles like this?
Upload your CV once. Get matched to relevant assignments automatically.