At a Glance
- Tasks: Design and optimise scalable data pipelines on AWS for data-driven decision making.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Flexible work options, continuous learning opportunities, and comprehensive wellbeing support.
- Other info: Be part of a diverse team committed to equal opportunities and personal growth.
- Why this job: Make an impact by working with cutting-edge cloud technologies and data solutions.
- Qualifications: Experience in data engineering or software engineering with a focus on data.
The predicted salary is between 45000 - 60000 € per year.
This role is key to supporting the design, development, and optimisation of scalable data pipelines and data platforms, enabling data‑driven decision making, analytics, and downstream applications. You will contribute to ensuring data quality, reliability, and performance through structured engineering and testing practices. Key technologies include AWS Glue, Python/PySpark, SQL, and configuration‑driven frameworks such as YAML.
Responsibilities
- Support delivery across data engineering and platform development initiatives.
- Collaborate with architects, engineers, and stakeholders to implement data solutions on AWS.
- Assist in planning and executing engineering tasks, releases, and deliverables.
- Build and maintain data pipelines and workflows on AWS platforms.
- Develop ETL/ELT pipelines using AWS Glue, Python/PySpark, SQL, and configuration‑driven frameworks.
- Support ingestion, transformation, and processing of structured and semi‑structured data.
- Contribute to the development of scalable, reusable data components and services.
- Test and validate data pipelines and processing jobs running on AWS services.
- Develop and execute data validation and reconciliation queries using SQL.
- Implement modern data platforms, including data lakes and lakehouse‑style architectures.
- Optimise data jobs for performance, scalability, and cost efficiency.
Qualifications
- Experience in data engineering or software engineering with a data focus.
- Strong interest in cloud‑based data platforms and distributed processing.
- Good analytical and problem‑solving skills.
- Attention to detail and commitment to data quality and reliability.
- Effective communication and teamwork skills.
- Willingness to learn and develop in AWS and modern data engineering practices.
Technical Expertise
- Hands‑on experience with AWS cloud services, especially AWS Glue, Python/PySpark, SQL querying, and data manipulation.
- Exposure to YAML or configuration‑driven pipelines (desirable).
- Experience building or supporting data pipelines and ETL/ELT processes.
- Familiarity with data lakes and/or lakehouse concepts and distributed processing frameworks such as Spark.
- Basic understanding of data architecture patterns and cloud‑native development.
- Experience with version control (e.g., Git) and CI/CD pipelines.
Benefits
We offer a range of tailored benefits that support your physical, emotional, and financial wellbeing. Our Learning and Development team ensures continuous growth and development opportunities, and we provide flexible work options. We are an equal opportunities employer and a proud Disability Confident Committed Employer. We guarantee an interview to applicants who declare to us that they have a disability and meet the minimum requirements for the role. If you require reasonable adjustments during the recruitment process, please let us know.
AWS Data Engineer in London employer: NTT DATA UK Ltd.
As an AWS Data Engineer with us, you'll thrive in a dynamic work culture that prioritises innovation and collaboration. We offer tailored benefits that enhance your wellbeing, alongside robust learning and development opportunities to foster your career growth. Join us in a supportive environment where your contributions directly impact data-driven decision-making and analytics.
StudySmarter Expert Advice🤫
We think this is how you could land AWS Data Engineer in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even online forums related to AWS and data engineering. You never know who might have a lead on your dream job!
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving AWS Glue, Python, and SQL. This is your chance to demonstrate your hands-on experience and problem-solving skills to potential employers.
✨Ace the Interview
Prepare for technical interviews by brushing up on your knowledge of data pipelines and AWS services. Practice common interview questions and be ready to discuss your past experiences and how they relate to the role.
✨Apply Through Our Website
Don’t forget to apply directly 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 AWS Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with AWS Glue, Python/PySpark, and SQL. 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! Use it to explain why you're passionate about data engineering and how you can contribute to our team. We love seeing enthusiasm and a bit of personality!
Showcase Your Problem-Solving Skills:In your application, mention specific examples where you've tackled challenges in data engineering. We appreciate candidates who can think critically and come up with innovative solutions!
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you get the best experience possible!
How to prepare for a job interview at NTT DATA UK Ltd.
✨Know Your Tech Stack
Make sure you’re well-versed in AWS Glue, Python/PySpark, and SQL. Brush up on how these technologies work together to build data pipelines. Being able to discuss your hands-on experience with these tools will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled data quality issues or optimised data jobs in the past. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will demonstrate your analytical skills and attention to detail.
✨Understand Data Architecture
Familiarise yourself with data lakes and lakehouse concepts, as well as distributed processing frameworks like Spark. Be ready to discuss how these concepts apply to the role and how you can contribute to building scalable data solutions.
✨Communicate Effectively
Since collaboration is key in this role, practice articulating your thoughts clearly. Be prepared to explain complex technical concepts in simple terms, especially when discussing your previous projects with architects and stakeholders.
