At a Glance
- Tasks: Design and build scalable data pipelines using AWS services for real-time insights.
- Company: Leading organisation in data and analytics with a modern cloud environment.
- Benefits: Up to £400 per day, hybrid work, and potential contract extension.
- Other info: Collaborative Agile environment with opportunities for continuous improvement.
- Why this job: Join high-impact projects that drive strategic business decisions and enhance your skills.
- Qualifications: Experience with AWS data services, Python programming, and ETL/ELT workflows.
The predicted salary is between 30000 - 40000 £ per year.
A leading organisation is seeking an experienced AWS Data Engineer to join their data and analytics team, contributing to the design, development and optimisation of large-scale data solutions within a modern cloud environment. This contract offers the opportunity to work on high-impact projects, delivering data platforms and pipelines that drive real-time insights and strategic business decisions.
Responsibilities for the AWS Data Engineer:
- Design, build and maintain scalable data pipelines and architectures within the AWS ecosystem
- Leverage services such as AWS Glue, Lambda, Redshift, EMR and S3 to support data ingestion, transformation and storage
- Work closely with data analysts, architects and business stakeholders to translate requirements into robust technical solutions
- Implement and optimise ETL/ELT processes, ensuring data integrity, consistency and quality across multiple sources
- Apply best practices in data modelling, version control, and CI/CD to deliver maintainable and reusable code
- Monitor data performance and reliability, proactively identifying opportunities to enhance efficiency and scalability
- Support the integration of data from diverse systems, including APIs and third-party platforms, into a unified architecture
- Ensure compliance with data governance, privacy and security policies throughout all stages of development
- Collaborate in an Agile environment, contributing to sprint planning, peer reviews and continuous improvement initiatives
Essential Skills for the AWS Data Engineer:
- Extensive hands-on experience with AWS data services
- Strong programming skills in Python (including libraries such as PySpark or Pandas)
- Solid understanding of data modelling, warehousing and architecture design within cloud environments
- Experience building and managing ETL/ELT workflows and data pipelines at scale
- Proficiency with SQL and working knowledge of relational and non-relational databases
- Experience deploying data infrastructure using IaC tools such as Terraform or CloudFormation
- Understanding of DevOps and CI/CD pipelines for data engineering solutions
- Strong problem-solving skills, with an ability to work both independently and collaboratively within multi-disciplinary teams
Desirable Skills for the AWS Data Engineer:
- Experience with Databricks, Kafka, or Kinesis for real-time data streaming
- Knowledge of containerisation (Docker, ECS) and modern orchestration tools such as Airflow
- Familiarity with machine learning model deployment pipelines or data lakehouse architectures
AWS Data Engineer - Real-Time Pipelines (Hybrid, London) employer: Involved Solutions
Join a leading organisation in Central London as an AWS Data Engineer, where you will be part of a dynamic data and analytics team dedicated to driving real-time insights through innovative data solutions. Enjoy a hybrid work model that promotes flexibility, alongside opportunities for professional growth and collaboration in an Agile environment. With competitive rates and the chance to work on high-impact projects, this role offers a rewarding experience in a vibrant city known for its tech advancements.
StudySmarter Expert Advice🤫
We think this is how you could land AWS Data Engineer - Real-Time Pipelines (Hybrid, London)
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and join online forums. 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 projects, especially those involving AWS data services. This gives potential employers a tangible look at what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to AWS and data engineering, and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace AWS Data Engineer - Real-Time Pipelines (Hybrid, London)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AWS Data Engineer role. Highlight your experience with AWS services and data pipelines, and don’t forget to mention any relevant projects you've worked on that align with the job description.
Showcase Your Skills:When writing your application, be sure to showcase your programming skills in Python and your experience with ETL/ELT processes. Use specific examples to demonstrate how you've applied these skills in real-world scenarios.
Keep It Clear and Concise:We love a well-structured application! Keep your writing clear and concise, focusing on the most relevant information. Avoid jargon unless it’s necessary, and make sure your passion for data engineering shines through.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Involved Solutions
✨Know Your AWS Services
Make sure you brush up on your knowledge of AWS services like Glue, Lambda, and Redshift. Be ready to discuss how you've used these tools in past projects, as this will show your practical experience and understanding of the AWS ecosystem.
✨Showcase Your Coding Skills
Since strong programming skills in Python are essential, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges that involve libraries like PySpark or Pandas to ensure you're sharp and ready.
✨Understand Data Pipelines Inside Out
Be prepared to talk about your experience with ETL/ELT processes and data pipelines. Think of specific examples where you’ve designed or optimised these workflows, and be ready to explain the impact your work had on data integrity and performance.
✨Emphasise Collaboration and Agile Experience
This role requires working closely with various stakeholders, so highlight your experience in Agile environments. Share examples of how you've contributed to sprint planning or peer reviews, showcasing your ability to work well in a team and adapt to changing requirements.
