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 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