At a Glance
- Tasks: Build and maintain data pipelines for analytics and machine learning.
- Company: Join a forward-thinking tech company focused on data innovation.
- Benefits: Attractive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with great potential for career advancement.
- Why this job: Make an impact by optimising data platforms and working with cutting-edge technologies.
- Qualifications: 6+ years in Data Engineering with skills in Python, PySpark, and AWS.
The predicted salary is between 60000 - 80000 £ per year.
We are on the lookout for a Senior Data Engineer with experience in PySpark, Python, and AWS to help us build scalable, high-quality data platforms.
Responsibilities:
- Build & maintain data pipelines for analytics and ML
- Orchestrate pipelines with Airflow
- Implement AWS services: Lambda, Redshift, S3
- Manage infrastructure with Terraform
- Set up CI/CD pipelines with GitHub Actions
- Optimize Spark jobs and troubleshoot issues
Qualifications:
- 6+ years in Data Engineering
- Proficiency in Python, PySpark, SQL, Spark, and Airflow
- AWS and Terraform experience
Data Engineer in London employer: Athsai
As a leading employer in the tech industry, we offer a dynamic work environment where innovation thrives. Our in-office culture fosters collaboration and creativity, providing employees with the opportunity to work closely with talented teams on cutting-edge data solutions. With a strong focus on professional development, we support our Data Engineers in enhancing their skills through training and access to the latest technologies, ensuring a rewarding career path in a vibrant location.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the hunt for a new role. Referrals can double your chances of landing an interview, so don’t be shy about asking for introductions.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with PySpark, Python, and AWS. This is your chance to demonstrate your expertise in building data pipelines and optimising Spark jobs, making you stand out to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of Airflow, Terraform, and CI/CD pipelines. Practise coding challenges and system design questions that are relevant to data engineering to ensure you're ready to impress.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented data engineers like you. Keep an eye on our listings and make sure your application stands out by tailoring it to each role.
We think you need these skills to ace Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with PySpark, Python, and AWS. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re passionate about data engineering and how your background makes you a perfect fit for our team. Keep it engaging and personal.
Showcase Your Projects:If you've worked on any cool data pipelines or ML projects, make sure to mention them! We love seeing real-world applications of your skills, especially with tools like Airflow and Terraform.
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 Athsai
✨Know Your Tech Stack
Make sure you’re well-versed in PySpark, Python, and AWS. Brush up on your knowledge of data pipelines and how to orchestrate them with Airflow. Being able to discuss specific projects where you've implemented these technologies will really impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've optimised Spark jobs or troubleshot issues in the past. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewers to see your thought process and impact.
✨Familiarise Yourself with CI/CD Practices
Since you'll be setting up CI/CD pipelines with GitHub Actions, it’s crucial to understand the principles behind continuous integration and deployment. Be ready to explain how you’ve used these practices in previous roles to enhance workflow efficiency.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s data architecture, team dynamics, or future projects. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
