As Data Engineer, you will promote data as a key differentiator for Nomia. You will help drive innovation and the building of intelligent systems for internal use, as well as for our customers and suppliers globally. You will be a key member of the team devoted to designing and implementing cutting-edge Agentic solutions.
* Design and implement data pipelines for cleaning and enriching data
* Be responsible for the data lake
* Find and curate third‑party datasets
* Design and maintain notebooks to measure the quality and completeness of data
* Understand real‑world use cases and translate them into actionable plans
* Conduct experiments to validate design choices or theories
* Create, manage, monitor, and maintain data models
* Design and implement ETL processes
* Document all aspects of your work
* Stay abreast of advancements in data engineering and research new software and techniques
* Participate in code reviews, technical discussions, and cross‑functional meetings
About You
* 3+ years' experience in data engineering
* Demonstrable experience with Microsoft Azure tools, such as Function Apps and services including Data Factory, Azure Synapse, and Azure Databricks
* Demonstrable experience designing and implementing ETL pipelines
* Proficient in PostgreSQL and T‑SQL
* Proficient in Python, with a strong command of data processing libraries such as Pandas and PySpark
* Proficient in the use of Python notebooks
* Experience with event‑driven architecture
* Familiarity with LLMs and prompt engineering
* Proficient in writing clean, maintainable code and well‑documented data pipelines
* Wide knowledge of different database types and designs
* Familiarity with data modelling techniques
* Genuine enthusiasm for learning new ideas and techniques
General
* Ensure compliance with Nomia's data protection and information security policies
* Hybrid work model — 3 days per week in office, with flexibility based on training or team needs
* Promote inclusivity, innovation, and ethical use of AI across the organisation
* Be adaptable and proactive in learning new tools, techniques, and methods as the AI landscape evolves
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