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- Tasks: Design large-scale data pipelines and collaborate with data scientists on exciting AI projects.
- Company: Freelance data hiring platform focused on innovative AI training.
- Benefits: $60 per hour, fully remote, flexible hours between 10 to 40 per week.
- Why this job: Join a cutting-edge team and shape the future of AI with your data expertise.
- Qualifications: Strong background in big data technologies and cloud platforms; BSc required.
- Other info: Flexible work environment with opportunities for professional growth.
The predicted salary is between 13 - 16 £ per hour.
A freelance data hiring platform is seeking a Data Engineer – AI Trainer. This role offers $60 per hour on a fully remote, hourly basis for 10 to 40 hours per week.
The ideal candidate will have a strong background in big data technologies like Hadoop and Spark, proven expertise with Kafka, and experience working with cloud platforms.
Responsibilities include:
- Designing large-scale data pipelines
- Collaborating with data scientists
A BSc in a related field is required.
Remote Data Engineer for AI Training & Big Data Pipelines employer: Data Freelance Hub
Contact Detail:
Data Freelance Hub Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Data Engineer for AI Training & Big Data Pipelines
✨Tip Number 1
Network like a pro! Reach out to fellow data engineers and AI enthusiasts on platforms like LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with big data technologies like Hadoop and Spark. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of Kafka and cloud platforms. We recommend doing mock interviews with friends or using online resources to build your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for talented individuals like you to join our team.
We think you need these skills to ace Remote Data Engineer for AI Training & Big Data Pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with big data technologies like Hadoop and Spark. We want to see how your skills align with the role, so don’t be shy about 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 makes you a perfect fit for our team. Keep it engaging and personal.
Showcase Your Technical Skills: Don’t forget to mention your expertise with Kafka and cloud platforms. We love seeing specific examples of how you've used these technologies in past roles, so include any relevant achievements or projects.
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!
How to prepare for a job interview at Data Freelance Hub
✨Know Your Tech Inside Out
Make sure you brush up on big data technologies like Hadoop and Spark, as well as Kafka. Be ready to discuss your hands-on experience with these tools and how you've used them in past projects.
✨Showcase Your Cloud Experience
Since the role involves working with cloud platforms, be prepared to talk about your experience with them. Highlight specific projects where you designed data pipelines in the cloud and the challenges you overcame.
✨Collaboration is Key
This position requires working closely with data scientists, so be ready to discuss how you've collaborated in the past. Share examples of how you’ve communicated complex data concepts to non-technical team members.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company’s data strategy and the team dynamics. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
