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For Companies At a Glance
- Tasks: Design and implement data pipelines, manage data lakes, and conduct experiments for innovative solutions.
- Company: Join Nomia, a forward-thinking company that values data as a key differentiator.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Embrace a culture of inclusivity and innovation while learning new tools in a dynamic environment.
- Why this job: Be at the forefront of data engineering and make a real impact on intelligent systems.
- Qualifications: 3+ years in data engineering with skills in Azure, Python, and ETL processes.
The predicted salary is between 50000 - 70000 £ per year.
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
Data Engineer employer: NOMIA
Contact Detail:
NOMIA Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving ETL processes or data pipelines. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss your past experiences in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight how your skills align with our mission and values.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Microsoft Azure tools and ETL pipelines, as these are key for us. Use specific examples that showcase your skills in data processing and Python.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our innovative projects. Mention any relevant experiences that align with our mission at Nomia.
Showcase Your Projects: If you've worked on interesting data projects, don’t hold back! Include links to your GitHub or any portfolios that demonstrate your coding skills and data pipeline designs. We love seeing real-world applications of your work!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at NOMIA
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals. Be ready to discuss your experience with ETL processes, data pipelines, and the tools mentioned in the job description, like Azure Data Factory and PostgreSQL. Having specific examples from your past work will show that you know your stuff!
✨Showcase Your Problem-Solving Skills
Prepare to talk about real-world use cases you've tackled. Think of a few scenarios where you had to design or implement a solution, and be ready to explain your thought process. This will demonstrate your ability to translate complex problems into actionable plans, which is key for this role.
✨Get Familiar with Their Tech Stack
Since the role involves using Microsoft Azure tools, make sure you’re comfortable discussing them. If you’ve worked with Azure Synapse or Databricks, have some examples ready. If not, do a bit of research to understand how they work and their applications in data engineering.
✨Emphasise Your Continuous Learning
Nomia values innovation and staying updated with advancements in data engineering. Share any recent courses, certifications, or projects that showcase your enthusiasm for learning new techniques. This will highlight your proactive approach and adaptability, which are crucial in the ever-evolving AI landscape.