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For Companies At a Glance
- Tasks: Design and implement data pipelines to ensure data integrity and accessibility.
- Company: Join Athsai, a forward-thinking company in the tech space.
- Benefits: Enjoy flexible working options and a collaborative team environment.
- Why this job: Be part of a dynamic team making an 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
Familiarise yourself with the specific AWS services mentioned in the job description. Understanding how to leverage these services effectively can set you apart during discussions.
✨Tip Number 2
Showcase your hands-on experience with PySpark and SQL by preparing examples of past projects. Be ready to discuss how you designed and implemented data pipelines in a practical context.
✨Tip Number 3
Brush up on your knowledge of CI/CD workflows, particularly using GitHub Actions. Being able to articulate your experience in setting up these workflows will demonstrate your technical proficiency.
✨Tip Number 4
Network with professionals in the data engineering field, especially those who work with AWS. Engaging in conversations can provide insights into the role and may even lead to referrals.
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 understand the key responsibilities and required skills for the Data Engineer position. Tailor your application to highlight your experience with PySpark, AWS, and ETL pipelines.
Highlight Relevant Experience: In your CV and cover letter, emphasise your hands-on experience with Python, SQL, and AWS services. Provide specific examples of projects where you designed and implemented data pipelines or used Terraform and GitHub Actions.
Craft a Strong Cover Letter: Write a compelling cover letter that connects your skills and experiences to the requirements of the job. Mention your familiarity with data governance and compliance standards if applicable, as this could set you apart from other candidates.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. 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
Make sure to highlight your proficiency in Python, PySpark, and SQL during the interview. Be prepared to discuss specific projects where you've implemented these technologies, as well as any challenges you faced and how you overcame them.
✨Demonstrate Your Understanding of AWS
Since the role requires extensive knowledge of AWS services, brush up on your understanding of cloud-native services and how they relate to data engineering. Be ready to explain how you've used AWS in previous roles, particularly in designing and deploying data pipelines.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. For instance, you might be asked how you would design an ETL pipeline for a specific use case. Practise articulating your thought process clearly and logically.
✨Familiarise Yourself with CI/CD Workflows
As the role involves setting up CI/CD workflows using GitHub Actions, ensure you understand the principles behind continuous integration and deployment. Be prepared to discuss your experience with version control and how it fits into the data engineering lifecycle.
