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For Companies At a Glance
- Tasks: Design and build cloud-based data platforms for analytics and reporting.
- Company: Join a forward-thinking tech company focused on data innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and enhance your skills in a supportive culture.
- Why this job: Make an impact by creating scalable data solutions in a dynamic environment.
- Qualifications: Experience in data engineering, SQL, Python, and cloud services required.
The predicted salary is between 50000 - 70000 £ per year.
This role is responsible for designing, building, and operating robust cloud-based data platforms that support large-scale analytics and reporting. You will work across the full data lifecycle, partnering closely with technical and non-technical stakeholders to deliver reliable, secure, and scalable data solutions.
Key Responsibilities
- Design, develop, and maintain scalable and reliable data pipelines using cloud-native services
- Build and optimise ETL/ELT workflows to support high-volume data ingestion and transformation
- Manage and process both structured and unstructured data, ensuring high standards of data quality and integrity
- Design and implement cloud-based data lake and data warehousing architectures
- Create and maintain analytical data marts using dimensional modelling techniques (e.g. star and snowflake schemas)
- Work collaboratively with analysts, data scientists, and business stakeholders to translate requirements into technical solutions
- Monitor, troubleshoot, and optimise data pipelines with a focus on performance and cost efficiency
- Implement Infrastructure as Code (IaC) to support consistent and repeatable deployments
- Integrate CI/CD pipelines and support modern DevOps practices
- Ensure compliance with data governance, security, and regulatory standards
- Produce clear and comprehensive documentation covering data architecture, pipelines, and engineering standards
Essential Skills and Experience
- Extensive experience in data engineering or related roles, including significant hands-on delivery within a cloud environment
- Strong practical experience with a broad range of cloud data and integration services
- Proven track record designing and implementing enterprise-scale data lakes and data warehouse solutions
- Advanced skills in SQL and Python, with experience using distributed processing frameworks such as Spark
- Demonstrated experience building analytical data marts and applying dimensional modelling principles
- Hands-on experience implementing Infrastructure as Code, ideally using Terraform or similar tooling
- Familiarity with DevOps concepts, CI/CD pipelines, and modern engineering practices
- Experience working with version control systems such as Git
- Strong analytical and problem-solving skills with a high level of attention to detail
Desirable Experience
- Relevant cloud or data certifications
- Background working in consulting or client-facing delivery environments
- Experience operating within large, complex, enterprise-scale data platforms
Data Engineer ( AWS) in City of London employer: Experis
Contact Detail:
Experis Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer ( AWS) in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Data Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, ETL workflows, and any cloud projects you've worked on. We want to see your hands-on experience, so make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL and Python skills, and be ready to discuss your experience with cloud services and data architecture. We recommend practicing common interview questions related to data engineering to boost your confidence.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for talented Data Engineers like you. Don’t miss out on the chance to join us and work on exciting cloud-based data solutions.
We think you need these skills to ace Data Engineer ( AWS) in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your cloud experience, data pipeline projects, and any relevant tools you've used. We want to see how you fit into our world!
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 aligns with our mission at StudySmarter. Keep it engaging and personal – we love a good story!
Showcase Your Projects: If you've worked on any cool data projects, don’t hold back! Include links or descriptions of your work, especially if it involves cloud-native services or ETL workflows. We’re keen to see what you can bring to the table!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of your application and ensures you get the attention you deserve. Plus, it’s super easy!
How to prepare for a job interview at Experis
✨Know Your Data Tools
Make sure you brush up on your knowledge of cloud data services, especially those related to AWS. Be ready to discuss your experience with ETL/ELT workflows and how you've optimised data pipelines in the past. This will show that you’re not just familiar with the tools but have hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in data engineering and how you tackled them. Highlight your analytical skills and attention to detail, as these are crucial for ensuring data quality and integrity. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Collaborate Like a Pro
Since this role involves working closely with both technical and non-technical stakeholders, be ready to discuss how you've successfully collaborated in the past. Share examples of how you translated complex technical requirements into understandable solutions for business users.
✨Understand Infrastructure as Code
Familiarise yourself with Infrastructure as Code concepts, particularly if you’ve used Terraform or similar tools. Be prepared to explain how you’ve implemented IaC in previous roles and how it contributes to consistent and repeatable deployments. This shows you’re aligned with modern engineering practices.