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For Companies At a Glance
- Tasks: Design and implement data pipelines to ensure data integrity and accessibility.
- Company: Join a forward-thinking company that values innovation and data-driven decisions.
- Benefits: Enjoy remote work flexibility and a competitive salary of £75k PA.
- Why this job: Be part of a dynamic team shaping the future of data engineering with cutting-edge technology.
- Qualifications: Proficient in PySpark, AWS, Python, SQL, and ETL pipeline design.
- Other info: Ideal for tech-savvy individuals eager to work with cloud-native services.
The predicted salary is between 60000 - 84000 £ 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
Pay range and compensation package: GBP 75k PA REMOTE in UK
Data Engineer AWS employer: Athsai
Contact Detail:
Athsai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer AWS
✨Tip Number 1
Familiarise yourself with the specific AWS services mentioned in the job description. Understanding how to leverage these services effectively will not only boost your confidence but also demonstrate your commitment to the role during any discussions.
✨Tip Number 2
Showcase your experience with PySpark and ETL pipelines by preparing examples of past projects. Be ready to discuss the challenges you faced and how you overcame them, as this will highlight your problem-solving skills and technical expertise.
✨Tip Number 3
Brush up on your knowledge of CI/CD workflows, particularly using GitHub Actions. Being able to articulate how you've implemented these processes in previous roles can set you apart from other candidates.
✨Tip Number 4
Network with professionals in the data engineering field, especially those who work with AWS. Engaging in conversations about industry trends and best practices can provide valuable insights and potentially lead to referrals for the position.
We think you need these skills to ace Data Engineer AWS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with PySpark, AWS, and ETL pipelines. Use specific examples to demonstrate your expertise in Python, SQL, and any relevant projects you've worked on.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about data engineering and how your skills align with the role. Mention your experience with cloud-native services and CI/CD workflows, as these are key aspects of the job.
Showcase Relevant Projects: If you have worked on projects involving Spark, Airflow, or Terraform, be sure to include these in your application. Describe your role and the impact of your contributions to highlight your hands-on experience.
Proofread and Edit: Before submitting your application, take the time to proofread your documents. Check for any spelling or grammatical errors, and ensure that your formatting is consistent and professional.
How to prepare for a job interview at Athsai
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in PySpark, AWS, and SQL. Bring examples of past projects where you designed and implemented ETL pipelines, as this will demonstrate your hands-on experience and technical expertise.
✨Understand the Company’s Data Needs
Research the company’s data architecture and any specific challenges they face. This will allow you to tailor your responses and show how your skills can directly address their needs.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Be ready to walk through how you would design a data pipeline or troubleshoot an issue using Spark or Airflow, showcasing your analytical thinking.
✨Demonstrate Your CI/CD Knowledge
Since the role involves setting up CI/CD workflows, be prepared to discuss your experience with GitHub Actions and Terraform. Highlight any relevant projects where you successfully deployed AWS resources.
