At a Glance
- Tasks: Build scalable data pipelines and ensure top-notch data quality using AWS technologies.
- Company: Join NTT America, a leader in Data & AI with a collaborative culture.
- Benefits: Enjoy flexible work options and opportunities for professional growth.
- Other info: Great opportunity for career advancement in the tech industry.
- Why this job: Make an impact by delivering high-performance data solutions in a dynamic environment.
- Qualifications: Experience in data engineering, especially with AWS Glue, Python, and SQL.
The predicted salary is between 50000 - 70000 € per year.
NTT America, Inc. is looking for a detail-oriented Data Engineer – AWS to support their Data & AI practice in Greater London. The successful candidate will develop scalable data pipelines, ensuring data quality and performance using AWS technologies.
The ideal applicant will have solid experience in data engineering, especially with AWS Glue, Python, and SQL. This position includes collaborative work with team members to deliver high-performance data solutions and offers flexible work options.
AWS Data Engineer — Flexible Work Options & Data Pipelines in London employer: NTT America, Inc.
NTT America, Inc. is an excellent employer that fosters a collaborative and innovative work culture, particularly for the AWS Data Engineer role in Greater London. With flexible work options and a strong focus on employee growth through continuous learning and development opportunities, NTT America empowers its team to excel in their careers while contributing to impactful data solutions.
StudySmarter Expert Advice🤫
We think this is how you could land AWS Data Engineer — Flexible Work Options & Data Pipelines in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at NTT America. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects using AWS Glue, Python, and SQL. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the interview by brushing up on common data engineering questions and AWS technologies. We recommend practising with friends or using mock interviews 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 love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace AWS Data Engineer — Flexible Work Options & Data Pipelines in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with AWS Glue, Python, and SQL. We want to see how your skills match the job description, 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 you can contribute to our Data & AI practice. Keep it engaging and personal.
Showcase Your Problem-Solving Skills:In your application, mention specific challenges you've tackled in data engineering. We love seeing how you approach problems and deliver high-performance solutions using AWS technologies.
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 NTT America, Inc.
✨Know Your AWS Stuff
Make sure you brush up on your AWS knowledge, especially AWS Glue. Be ready to discuss how you've used it in past projects and the impact it had on data quality and performance.
✨Show Off Your Python Skills
Prepare to talk about your experience with Python in data engineering. Have examples ready that showcase your ability to write efficient code for data pipelines and how you've tackled challenges using Python.
✨SQL is Key
Since SQL is crucial for this role, be prepared to answer technical questions or even solve problems on the spot. Practise writing queries and think about how you've optimised them in previous roles.
✨Collaboration is Everything
This position involves teamwork, so be ready to share examples of how you've successfully collaborated with others. Highlight any experiences where you worked with cross-functional teams to deliver data solutions.
