Senior Data Engineer designing and scaling advanced data platforms for 5G and future 6G innovations at Nokia. Building robust data pipelines while collaborating with Data Scientists and Engineers in a hybrid setting.
Responsibilities
Design, implement, and own scalable, reliable data pipelines supporting machine learning and analytics use cases
Define and evolve data architecture, ensuring high data quality, consistency, and availability across systems
Lead complex data transformations, including cleaning, aggregation, enrichment, and feature engineering for ML workloads
Optimize data processing and storage solutions for performance and cost efficiency, including effective use of GPU resources
Collaborate closely with Data Scientists, SW Engineers, and System Architects to align data solutions with modeling and product needs
Drive technical decisions and best practices, contributing to architecture reviews, design discussions, and test strategies
Mentor and support less experienced engineers, promoting high engineering standards and knowledge sharing
Identify and proactively resolve technical risks and bottlenecks in data and ML workflows
Requirements
Several years of hands-on experience as a Data Engineer or similar position in production-grade environments
Strong proficiency in Python, with solid software engineering practices
Proven experience in designing and maintaining large-scale data pipelines and data platforms
Deep understanding of data transformation, enrichment, and feature preparation for machine learning use cases
Experience working closely with Data Scientists and SW Engineers in end-to-end ML workflows
Very good English skills, both written and spoken
A proactive mindset with strong ownership, problem-solving, and collaboration skills
It would be nice if you also had:
Knowledge of 5G networks, especially the physical layer and performance-related aspects
Experience with GPU-accelerated data processing or high-performance computing environments
Familiarity with ML model development, deployment, and optimization
Experience in technical leadership, including mentoring or leading complex initiatives
Exposure to cloud-native data architectures and cost optimization strategies
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