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Data Engineer
Senior Data Engineer
About the Role
As a Data Engineer, you will help promote data as a key differentiator for Nomia. You will drive innovation and build intelligent systems for internal use, customers, and suppliers globally. This role involves being a key member of a team focused on designing and implementing cutting-edge Agentic solutions.
Responsibilities
- Design and implement data pipelines for cleaning and enriching data
- Oversee the data lake infrastructure
- Locate and curate third-party datasets
- Prepare data for experimental use cases
- Design and maintain notebooks to measure data quality and completeness
- Translate real-world use cases 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 work clearly and comprehensively
- Stay updated on advancements in data engineering and explore new software tools and techniques
- Participate in code reviews, technical discussions, and cross-functional meetings
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About You
Experience & Technical Requirements
- 3+ years’ experience in data engineering
- Hands-on experience with Microsoft Azure tools, including:
- Function Apps
- Azure Data Factory
- Azure Synapse
- Azure Databricks
- ETL pipeline design and implementation expertise
- Proficiency in:
- PostgreSQL and T-SQL
- Python, with expertise in data processing libraries (e.g., Pandas, PySpark)
- Python notebooks for data exploration and analysis
- Experience with event-driven architecture
- Familiarity with LLMs and prompt engineering
- Ability to write clean, maintainable code and create well-documented pipelines
- Broad knowledge of database types and design principles
- Experience with data modelling techniques
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Soft Skills & Attitude
- Strong enthusiasm for learning new ideas and techniques
- Adaptability in emerging AI tools and methodologies
General
- Ensure compliance with Nomia’s data protection and information security policies
- Hybrid work model: 3 days per week in-office (flexibility for training or team needs)
- Support inclusivity, innovation, and ethical AI use across the organization
- Proactive in adopting new tools, techniques, and methods as the AI landscape evolves
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