Job description
About the Role
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.
Roles & Responsibilities Design and implement data pipelines for cleaning and enriching data Be responsible for the data lake Find and curate third-party datasets Prepare data for use in experiments 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 Py.
Spark 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