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- Tasks: Build and enhance data pipelines while contributing to analytics and AI projects.
- Company: Leading UK technology firm focused on data-driven innovation.
- Benefits: Competitive salary of £80,000, remote work flexibility, and growth opportunities.
- Why this job: Join a fast-growing company where your work directly impacts innovation and product development.
- Qualifications: Strong SQL and Python skills, plus experience with AWS and data workflows.
- Other info: Dynamic environment with a focus on evolving data infrastructure.
The predicted salary is between 48000 - 72000 £ per year.
A leading technology firm in the UK is seeking a Data Engineer (AWS) to build and improve data pipelines, contribute to analytics and AI initiatives, and evolve the company's AWS-based data infrastructure.
This role, offering a competitive salary of £80,000 and remote work flexibility, is ideal for someone with strong SQL and Python skills alongside experience in AWS and data workflows.
Join a fast-growing company where data drives innovation and product development.
Remote AWS Data Engineer: Pipelines & Analytics employer: Jefferson Frank
Contact Detail:
Jefferson Frank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote AWS Data Engineer: Pipelines & Analytics
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at tech meetups. 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 AWS projects, data pipelines, and any analytics work you've done. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL and Python skills, and be ready to discuss your experience with AWS. Practice common interview questions and think about how your past projects relate to the role.
✨Tip Number 4
Apply through our website! We make it easy for you to find roles that match your skills. Plus, applying directly shows your enthusiasm for joining our team and helps us get to know you better.
We think you need these skills to ace Remote AWS Data Engineer: Pipelines & Analytics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, SQL, and Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about the Data Engineer role and how you can contribute to our analytics and AI initiatives. Keep it engaging and personal.
Showcase Your Projects: If you've worked on any data pipelines or analytics projects, make sure to mention them in your application. We love seeing real-world examples of your work and how you’ve tackled challenges in the past.
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 this exciting opportunity. Plus, it’s super easy!
How to prepare for a job interview at Jefferson Frank
✨Know Your AWS Inside Out
Make sure you brush up on your AWS knowledge before the interview. Familiarise yourself with services like S3, Redshift, and Lambda, as well as best practices for building data pipelines. Being able to discuss how you've used these tools in past projects will really impress them.
✨Show Off Your SQL and Python Skills
Prepare to demonstrate your SQL and Python expertise during the interview. You might be asked to solve a problem or optimise a query on the spot, so practice common scenarios beforehand. Having examples of how you've used these skills in real-world applications can set you apart.
✨Understand Data Workflows
Get a solid grasp of data workflows and ETL processes. Be ready to discuss how you’ve designed or improved data pipelines in previous roles. Highlight any experience you have with analytics and AI initiatives, as this aligns perfectly with what they’re looking for.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company's data strategy and future projects. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you. Plus, it gives you a chance to showcase your knowledge about the industry.