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- Tasks: Design and optimise data pipelines while collaborating with Data Science teams.
- Company: Fast-growing tech company in the UK with a focus on innovation.
- Benefits: Competitive salary, flexible perks, and paid holidays.
- Why this job: Join a dynamic team and work on cutting-edge data engineering projects.
- Qualifications: Experience in dbt, Python, SQL, and understanding of ML Ops principles.
- Other info: Great opportunity for career growth in a supportive environment.
The predicted salary is between 50000 - 65000 £ per year.
A fast-growing tech company in the UK is seeking a Core Data Engineer to design, build, and optimize data pipelines. This role involves implementing scalable ELT/ETL frameworks and collaborating with Data Science teams. Ideal candidates will have experience in dbt, Python, and SQL, as well as a strong understanding of data architecture and ML Ops principles. Competitive salary and benefits including flexible perks and paid holidays are offered.
Data Engineer — Scalable Pipelines, GenAI & ML Ops in London employer: Fospha Marketing
Contact Detail:
Fospha Marketing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer — Scalable Pipelines, GenAI & ML Ops in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in data engineering. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving dbt, Python, and SQL. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ELT/ETL frameworks and ML Ops principles. Practise coding challenges and be ready to discuss your thought process during problem-solving.
✨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 love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer — Scalable Pipelines, GenAI & ML Ops in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with dbt, Python, and SQL. We want to see how your skills align with the role of a Core Data Engineer, so don’t hold back on showcasing 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 your background in ML Ops can contribute to our team. Keep it engaging and personal!
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in building or optimising data pipelines. We love seeing candidates who can think critically and creatively about data architecture.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and we can’t wait to see what you bring to the table!
How to prepare for a job interview at Fospha Marketing
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of data architecture and the specific tools mentioned in the job description, like dbt, Python, and SQL. Be ready to discuss how you've used these technologies in past projects, as this will show your practical experience.
✨Showcase Your Problem-Solving Skills
Prepare to talk about challenges you've faced while designing or optimising data pipelines. Think of specific examples where you implemented scalable ELT/ETL frameworks and how you collaborated with Data Science teams to overcome obstacles.
✨Understand ML Ops Principles
Since the role involves ML Ops, make sure you can explain key concepts and how they relate to data engineering. Familiarise yourself with best practices in deploying machine learning models and be ready to discuss how you would integrate these into your data pipelines.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's data strategy, team dynamics, and future projects. This not only shows your interest but also helps you gauge if the company is the right fit for you.