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- Tasks: Design and implement data pipelines, manage data lakes, and drive innovation in intelligent systems.
- Company: Join Nomia, a forward-thinking company prioritising 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 continuous learning in a dynamic environment.
- Why this job: Make a real impact by working on cutting-edge data engineering projects.
- Qualifications: 3+ years in data engineering with skills in Azure, Python, and ETL processes.
The predicted salary is between 50000 - 65000 £ per year.
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
Data Engineer employer: Nomia Ltd
Contact Detail:
Nomia Ltd 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 folks in the data engineering field on LinkedIn or at meetups. We can’t stress enough how personal connections can lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, ETL processes, and any cool projects you've worked on. We love seeing real-world applications of your expertise, so make it shine!
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your experience with Azure tools and Python libraries. We recommend practicing common data engineering scenarios to impress your interviewers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always looking for passionate individuals who want to drive innovation in data engineering.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data engineering, especially with Microsoft Azure tools and ETL pipelines. We want to see how your skills align with what we're looking for, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our innovative team. We love seeing genuine enthusiasm, so let your personality come through!
Showcase Your Projects: If you've worked on any cool data projects, make sure to mention them! Whether it's designing data pipelines or using Python libraries like Pandas, we want to know what you've done and how it relates to the role.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and you’ll be good to go!
How to prepare for a job interview at Nomia Ltd
✨Know Your Data Engineering Stuff
Make sure you brush up on your data engineering skills, especially with Microsoft Azure tools like Data Factory and Azure Databricks. Be ready to discuss your experience designing ETL pipelines and how you've used Python libraries like Pandas and PySpark in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in previous roles and how you tackled them. Think of examples where you translated complex use cases into actionable plans or conducted experiments to validate your design choices. This will show your analytical thinking and creativity.
✨Be Ready for Technical Discussions
Expect to engage in technical discussions during the interview. Brush up on your knowledge of data models, event-driven architecture, and data modelling techniques. Being able to articulate your thought process during code reviews or technical debates will impress the interviewers.
✨Demonstrate Your Enthusiasm for Learning
Nomia values a genuine enthusiasm for learning new ideas and techniques. Share examples of how you've kept up with advancements in data engineering or any new software you've explored. This shows that you're proactive and adaptable, which is key in the ever-evolving AI landscape.