Senior Data Engineer: PySpark, AWS & Airflow Lead
Senior Data Engineer: PySpark, AWS & Airflow Lead

Senior Data Engineer: PySpark, AWS & Airflow Lead

Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop scalable data platforms and maintain data pipelines using cutting-edge technologies.
  • Company: Leading tech company in the UK with a dynamic team culture.
  • Benefits: Competitive salary, career growth opportunities, and a collaborative work environment.
  • Why this job: Join a dynamic team and enhance your career while working with innovative data solutions.
  • Qualifications: 6+ years in Data Engineering with skills in Python, PySpark, SQL, and Airflow.
  • Other info: Opportunity to work with AWS and Terraform in a fast-paced environment.

The predicted salary is between 43200 - 72000 £ per year.

A leading tech company in the United Kingdom is looking for a Senior Data Engineer to develop scalable data platforms. The successful candidate will have at least 6 years of experience in Data Engineering, skilled in Python, PySpark, SQL, and Airflow, and familiar with AWS and Terraform.

Responsibilities include:

  • Maintaining data pipelines
  • Orchestrating tasks with Airflow
  • Implementing various AWS services

This is a great opportunity to join a dynamic team and enhance your career.

Senior Data Engineer: PySpark, AWS & Airflow Lead employer: Athsai

Join a leading tech company in the UK that prioritises innovation and employee development. With a vibrant work culture that fosters collaboration and creativity, you'll have access to cutting-edge projects and opportunities for professional growth. Enjoy competitive benefits and the chance to work with a talented team dedicated to pushing the boundaries of technology.
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Contact Detail:

Athsai Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior Data Engineer: PySpark, AWS & Airflow Lead

✨Tip Number 1

Network like a pro! Reach out to your connections in the tech industry, especially those who work with data engineering. A friendly chat can lead to insider info about job openings or even referrals.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects with PySpark, AWS, and Airflow. This gives potential employers a taste of what you can do and sets you apart from the crowd.

✨Tip Number 3

Prepare for technical interviews by brushing up on your SQL and Python skills. Practice common data engineering problems and be ready to discuss your past experiences with data pipelines and AWS services.

✨Tip Number 4

Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented folks like you. Plus, it’s a great way to ensure your application gets noticed by the right people.

We think you need these skills to ace Senior Data Engineer: PySpark, AWS & Airflow Lead

Data Engineering
Python
PySpark
SQL
Airflow
AWS
Terraform
Data Pipeline Maintenance
Task Orchestration
Cloud Services Implementation

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your experience with Python, PySpark, SQL, and Airflow. 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 your experience with AWS and Terraform makes you a perfect fit for our team.

Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in data engineering. We love seeing how you approach problems and implement solutions, especially when it comes to maintaining data pipelines.

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 Python, PySpark, SQL, and Airflow. Brush up on your AWS and Terraform knowledge too. Be ready to discuss how you've used these technologies in past projects, as this will show your practical experience.

✨Showcase Your Problem-Solving Skills

Prepare to talk about specific challenges you've faced in data engineering and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easier for the interviewer to follow your thought process.

✨Understand the Company’s Data Needs

Research the company’s current data platforms and any recent projects they’ve undertaken. This will help you tailor your responses to demonstrate how your skills can directly benefit their operations and align with their goals.

✨Ask Insightful Questions

Prepare a few thoughtful questions about the team dynamics, the tech stack they use, or upcoming projects. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.

Senior Data Engineer: PySpark, AWS & Airflow Lead
Athsai

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