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- Tasks: Design and optimize scalable data pipelines for a sports analytics platform.
- Company: Join a rapidly expanding sports analytics company based in London Bridge.
- Benefits: Enjoy a hybrid work model, competitive salary, bonuses, and additional benefits.
- Why this job: Make a significant impact in a fast-paced, data-driven environment with a focus on innovation.
- Qualifications: Strong background in data architecture, AWS technologies, and proficiency in SQL required.
- Other info: Passion for sports analytics is a plus; apply by sending your CV to Rishi Chudasama.
The predicted salary is between 40000 - 60000 £ per year.
Mid Level AWS Data Engineer – Sports Analytics Platform – London (Hybrid)
(Tech stack: Senior AWS Data Engineer, AWS, Data Modelling, S3, Data Architecture, Lambda, Athena, SQL, Python, C#, Snowflake, Data Pipelines, Architecture, Cloud, Data Engineering, DevOps)
Our client, an exciting and rapidly expanding sports analytics company based in London Bridge, is seeking a Mid Level AWS Data Engineer with a strong data architecture background to join their team on a permanent basis. This is a crucial role in driving the structural integrity and scalability of the company’s data engineering processes, ensuring the platform is robust and capable of growing with the business.
As an AWS Data Engineer, you will be help with designing and optimising scalable data pipelines, ensuring that the data systems are architecturally sound and maintainable. You’ll play a key role in improving data structures, documenting processes, and working closely with other teams to implement best practices in data modelling, debugging, and optimisation.
Key Responsibilities:
Contribute to the development of scalable, architecturally sound data pipelines, ensuring AWS data structures (S3, Lambda, Athena) are optimised for performance and stability.
Design and implement data models that are fit for various use cases, ensuring structural integrity across the data engineering landscape.
Debug and optimise data pipelines and queries to improve performance and address bottlenecks.
Maintain clean, well-documented systems, with a focus on logging and reproducibility.
Collaborate with development and engineering teams to enhance the overall data architecture and ensure scalability of the platform.
Essential Skills:
Strong background in data architecture and data modelling, with proven experience in designing scalable data pipelines.
Knowledge of C#.
Deep expertise in AWS technologies, including S3, Lambda, and Athena.
Proficiency in SQL, with the ability to optimise complex queries.
Passion for clean systems, with a focus on documentation and maintaining reproducibility.
Enthusiasm for building scalable, efficient systems that are designed for growth and maintainability.
Desirable Skills:
Experience with Snowflake.
Knowledge of Python.
An interest in sports analytics and working within a data-driven environment.
Location: London (Hybrid – 1-2 days a week in the office)
Salary: £50,000 – £60,000 + Bonus + Benefits
This is an outstanding opportunity for a Mid Level AWS Data Engineer with a passion for data architecture to make a significant impact in an innovative sports analytics company. If you’re excited about working in a fast-paced, data-driven environment, we’d love to hear from you!
To apply for this position, please send your CV to Rishi Chudasama at Noir.
Noir continues to be the leading Microsoft recruitment agency; we can help you make the right career decisions!
AWS Data Engineer employer: Noir
Contact Detail:
Noir Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Data Engineer
✨Tip Number 1
Familiarize yourself with the specific AWS services mentioned in the job description, such as S3, Lambda, and Athena. Having hands-on experience or projects that showcase your skills with these technologies will make you stand out.
✨Tip Number 2
Highlight any experience you have with data architecture and data modeling. Be prepared to discuss how you've designed scalable data pipelines in previous roles, as this is a key responsibility of the position.
✨Tip Number 3
Show your enthusiasm for sports analytics! Research the company and its projects, and be ready to share your thoughts on how data can drive insights in the sports industry during your conversations.
✨Tip Number 4
Network with professionals in the data engineering field, especially those who work with AWS technologies. Engaging with the community can provide valuable insights and potentially lead to referrals.
We think you need these skills to ace AWS Data Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Mid Level AWS Data Engineer position. Familiarize yourself with the key technologies mentioned in the job description, such as AWS, S3, Lambda, and Athena.
Tailor Your CV: Customize your CV to highlight your experience with data architecture, data modelling, and AWS technologies. Emphasize any relevant projects or roles that demonstrate your ability to design scalable data pipelines and optimize performance.
Craft a Strong Cover Letter: Write a compelling cover letter that showcases your passion for data engineering and your interest in sports analytics. Mention specific skills and experiences that align with the job description, and explain why you would be a great fit for the company.
Highlight Relevant Skills: In your application, make sure to clearly list your proficiency in SQL, C#, and any experience with Python or Snowflake. Provide examples of how you've used these skills in previous roles to solve problems or improve processes.
How to prepare for a job interview at Noir
✨Showcase Your Data Architecture Skills
Be prepared to discuss your experience with data architecture and modelling. Highlight specific projects where you designed scalable data pipelines, and explain the challenges you faced and how you overcame them.
✨Demonstrate AWS Expertise
Since the role requires deep knowledge of AWS technologies like S3, Lambda, and Athena, make sure to provide examples of how you've used these tools in past projects. Discuss any optimizations you implemented to improve performance.
✨Prepare for Technical Questions
Expect technical questions related to SQL and data pipeline optimization. Brush up on complex query optimization techniques and be ready to solve problems on the spot, as this will showcase your analytical skills.
✨Express Your Passion for Sports Analytics
Since the company focuses on sports analytics, share your enthusiasm for the field. Discuss any relevant experiences or projects that demonstrate your interest in data-driven environments, especially in sports.
