Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and implement data pipelines, ensuring data integrity and accessibility.
- Company: Join Athsai, a dynamic company focused on innovative data solutions.
- Benefits: Enjoy flexible working options and a collaborative team environment.
- Why this job: Be part of a cutting-edge team making a real impact in data engineering.
- Qualifications: Proficient in Python, PySpark, SQL, and AWS; experience with ETL pipelines required.
- Other info: EU work permit is necessary for this role.
The predicted salary is between 36000 - 60000 £ per year.
About the Role
The Data Engineer will play a crucial role in designing and implementing robust data pipelines, ensuring the integrity and accessibility of data across various platforms.
Required Skills
- Proficient in PySpark and AWS
- Strong experience in designing, implementing, and debugging ETL pipelines
- Expertise in Python, PySpark, and SQL
- In-depth knowledge of Spark and Airflow
- Experience in designing data pipelines using cloud-native services on AWS
- Extensive knowledge of AWS services
- Experience in deploying AWS resources using Terraform
- Hands-on experience in setting up CI/CD workflows using GitHub Actions
Preferred Skills
- Experience with additional cloud platforms
- Familiarity with data governance and compliance standards
Data Engineer , Python, PySpark, and SQL, AWS employer: JR United Kingdom
Contact Detail:
JR United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer , Python, PySpark, and SQL, AWS
✨Tip Number 1
Network with professionals in the data engineering field, especially those who work with AWS and PySpark. Join relevant online communities or forums where you can ask questions and share insights, as this can lead to valuable connections and potential job referrals.
✨Tip Number 2
Showcase your hands-on experience with AWS services by working on personal projects or contributing to open-source projects. This practical experience will not only enhance your skills but also provide concrete examples to discuss during interviews.
✨Tip Number 3
Prepare for technical interviews by practising common data engineering problems, particularly those involving ETL processes and data pipeline design. Use platforms like LeetCode or HackerRank to sharpen your coding skills in Python and SQL.
✨Tip Number 4
Familiarise yourself with Terraform and CI/CD workflows, as these are crucial for deploying AWS resources. Consider taking online courses or tutorials that focus on these tools to demonstrate your commitment to continuous learning in your application.
We think you need these skills to ace Data Engineer , Python, PySpark, and SQL, AWS
Some tips for your application 🫡
Understand the Role: Read the job description thoroughly to grasp the key responsibilities and required skills for the Data Engineer position. Highlight your experience with PySpark, AWS, and ETL pipelines in your application.
Tailor Your CV: Customise your CV to reflect your proficiency in Python, SQL, and AWS. Include specific examples of projects where you designed and implemented data pipelines, showcasing your technical skills and achievements.
Craft a Compelling Cover Letter: Write a cover letter that connects your background to the job requirements. Emphasise your hands-on experience with AWS services and CI/CD workflows, and explain why you're excited about the opportunity at Athsai.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail, which is crucial for a Data Engineer role.
How to prepare for a job interview at JR United Kingdom
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, PySpark, and SQL in detail. Bring examples of projects where you've designed and implemented ETL pipelines, as this will demonstrate your hands-on expertise.
✨Understand AWS Services
Familiarise yourself with the specific AWS services mentioned in the job description. Be ready to explain how you've used these services in past projects, particularly in relation to data pipelines and cloud-native solutions.
✨Discuss CI/CD Workflows
Since the role involves setting up CI/CD workflows using GitHub Actions, be prepared to talk about your experience with version control and automation. Highlight any challenges you faced and how you overcame them.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think about common issues in data engineering, such as data integrity or pipeline failures, and how you would address them using your technical knowledge.
