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- Tasks: Design and maintain data pipelines while collaborating with DevOps teams.
- Company: A leading data solutions provider focused on innovation.
- Benefits: Remote work, competitive salary, and a dynamic project environment.
- Why this job: Join a team that drives data-driven projects and makes an impact.
- Qualifications: 3+ years of experience in data engineering, SQL, and cloud services.
- Other info: Exciting opportunities for growth in a fast-paced industry.
The predicted salary is between 36000 - 60000 £ per year.
A data solutions provider is seeking a skilled Data Engineer to design and maintain data pipelines. This role involves collaboration with DevOps teams and requires advanced SQL and experience with BigQuery. The position is remote, offering a dynamic environment focused on data-driven projects. Candidates should have at least 3 years of experience in the field, with proficiency in cloud services and ETL tools.
Remote Data Engineer: Cloud Pipelines & BigQuery employer: Talenzon group
Contact Detail:
Talenzon group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Data Engineer: Cloud Pipelines & BigQuery
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with cloud services and BigQuery. A friendly chat can lead to insider info about job openings that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and any projects you've worked on. This is your chance to demonstrate your SQL prowess and experience with ETL tools, making you stand out to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions. We recommend practising your answers to technical scenarios, especially those involving collaboration with DevOps teams. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive and eager to join our dynamic, data-driven environment.
We think you need these skills to ace Remote Data Engineer: Cloud Pipelines & BigQuery
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data pipelines, SQL, and BigQuery. We want to see how your skills match the role, so don’t be shy about showcasing relevant projects you've worked on!
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 makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Technical Skills: Since this role requires advanced SQL and cloud services knowledge, make sure to mention specific tools and technologies you’ve used. We love seeing concrete examples of your work with ETL tools and cloud platforms!
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Talenzon group
✨Know Your SQL Inside Out
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss complex queries and how you've used SQL in past projects. Practising with sample datasets can help you articulate your thought process during the interview.
✨Familiarise Yourself with BigQuery
Since this role specifically mentions BigQuery, it’s crucial to understand its features and functionalities. Try to work on a small project using BigQuery if you can, so you can share your hands-on experience and insights during the interview.
✨Collaboration is Key
This position involves working closely with DevOps teams, so be ready to discuss your experience in collaborative environments. Think of examples where you’ve successfully worked with cross-functional teams to deliver data solutions.
✨Showcase Your ETL Expertise
As the role requires experience with ETL tools, prepare to talk about the ETL processes you've implemented. Highlight any challenges you faced and how you overcame them, as well as the impact your work had on data quality and accessibility.
